Selected Publications

Year	Details	URL/PDF
2024	Waller, M., Rodrigues, O. and Cocarascu, O., Identifying Reasons for Bias: An Argumentation-Based Approach, Association for the Advancement of Artificial Intelligence, DOI: 10.1609/aaai.v38i19.30165, 2024. [Abstract] [BibTeX]	URL PDF
Abstract: As algorithmic decision-making systems become more prevalent in society, ensuring the fairness of these systems is becoming increasingly important. Whilst there has been substantial research in building fair algorithmic decision-making systems, the majority of these methods require access to the training data, including personal characteristics, and are not transparent regarding which individuals are classified unfairly. In this paper, we propose a novel model-agnostic argumentation-based method to determine why an individual is classified differently in comparison to similar individuals. Our method uses a quantitative argumentation framework to represent attribute-value pairs of an individual and of those similar to them, and uses a well-known semantics to identify the attribute-value pairs in the individual contributing most to their different classification. We evaluate our method on two datasets commonly used in the fairness literature and illustrate its effectiveness in the identification of bias.
BibTeX: @inbook{aaai-24, author = {Madeleine Waller and Odinaldo Rodrigues and Oana Cocarascu}, title = {Identifying Reasons for Bias: An Argumentation-Based Approach}, booktitle = {Association for the Advancement of Artificial Intelligence}, publisher = {AAAI Press}, year = {2024}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/30165}, doi = {https://doi.org/10.1609/aaai.v38i19.30165} }
2024	Baumann, R., Berthold, M., Gabbay, D.M. and Rodrigues, O., Forgetting in Abstract Argumentation: Limits and Possibilities, Journal of Artificial Intelligence Research, 2024. [Abstract] [BibTeX]
Abstract: The topic of forgetting, which loosely speaking means losing, removing, or even hiding some variables, propositions, or formulas, has been extensively studied in the field of knowledge representation and reasoning for many major formalisms. In this article, we convey this topic to the highly active field of abstract argumentation. We provide an in-depth analysis of desirable syntactical and/or semantical properties of possible forgetting operators. In doing so, we included well-known logic programming conditions, such as strong persistence or strong invariance. Further, we argue that although abstract argumentation and logic programming are closely related, it is not possible to reduce forgetting in abstract argumentation to forgetting in logic programming in a straightforward manner. The analysis of desiderata, adapted to the specifics of abstract argumentation, includes implications among them, individual and collective satisfiability, and identifying inherent limits for a set of prominent semantics. Finally, we conduct a case study on stable semantics, incorporating concrete forgetting operators.
BibTeX: @article{bbgr:24, author = {R. Baumann, M. Berthold, D. M. Gabbay, O. Rodrigues}, title = {Forgetting in Abstract Argumentation: Limits and Possibilities}, journal = {Journal of Artificial Intelligence Research}, year = {2024}, note = {To appear} }
2024	Waller, M., Rodrigues, O., Lee, M.S.A. and Cocarascu, O., Bias Mitigation Methods: Applicability, Legality, and Recommendations for Development, Journal of Artificial Intelligence Research, Vol. 81, 2024. [Abstract] [BibTeX]
Abstract: As algorithmic decision-making systems (ADMS) are increasingly deployed across var- ious sectors, the importance of research on fairness in Artificial Intelligence (AI) continues to grow. In this paper we highlight a number of significant practical limitations and regula- tory compliance issues associated with the application of existing bias mitigation methods to ADMS. We present an example of an algorithmic system used in recruitment to illustrate these limitations. Our analysis of existing methods indicates a pressing need for a change in the approach to the development of new methods. In order to address the limitations, we provide recommendations for key factors to consider in the development of new bias mitigation methods that aim to be effective in real-world scenarios and comply with legal requirements in the European Union, United Kingdom and United States, such as non-discrimination, data protection and sector-specific regulations. Further, we suggest a checklist relating to these recommendations that should be included with the development of new bias mitigation methods.
BibTeX: @article{bias:24, author = {Madeleine Waller, Odinaldo Rodrigues, Michelle Seng Ah Lee, Oana Cocarascu}, title = {Bias Mitigation Methods: Applicability, Legality, and Recommendations for Development}, journal = {Journal of Artificial Intelligence Research}, year = {2024}, volume = {81}, note = {To Appear} }
2024	Schneider Gavenski, G., Monteiro, J., Meneguzzi, F., Luck, M. and Rodrigues, O., Explorative Imitation Learning: A Path Signature Approach for Continuous Environments, 27th European Conference on Artificial Intelligence, DOI: 10.3233/faia240660, 2024. [Abstract] [BibTeX]	URL PDF
Abstract: Some imitation learning methods combine behavioural cloning with self-supervision to infer actions from state pairs. How- ever, most rely on a large number of expert trajectories to increase generalisation and human intervention to capture key aspects of the problem, such as domain constraints. In this paper, we propose Continuous Imitation Learning from Observation (CILO), a new method augmenting imitation learning with two important features: (i) exploration, allowing for more diverse state transitions, requiring less expert trajectories and resulting in fewer training iterations; and (ii) path signatures, allowing for automatic encoding of constraints, through the creation of non-parametric representations of agents and expert trajectories. We compared CILO with a baseline and two leading imitation learning methods in five environments. It had the best overall performance of all methods in all environments, outperforming the expert in two of them.
BibTeX: @inbook{gavenski-et-al:24, author = {Schneider Gavenski, Gavenski and Juarez Monteiro and Felipe Meneguzzi and Michael Luck and Odinaldo Rodrigues}, title = {Explorative Imitation Learning: A Path Signature Approach for Continuous Environments}, booktitle = {27th European Conference on Artificial Intelligence}, publisher = {IOS Press}, year = {2024}, note = {ECAI 2004 ; Conference date: 01-01-2004}, url = {https://kclpure.kcl.ac.uk/portal/en/publications/explorative-imitation-learning-a-path-signature-approach-for-cont}, doi = {https://doi.org/10.3233/faia240660} }
2024	Gavenski, N., Luck, M. and Rodrigues, O., Imitation Learning Datasets: A Toolkit For Creating Datasets, Training Agents and Benchmarking, Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, DOI: 10.5555/3635637.3663292, 2024. [Abstract] [BibTeX]	URL PDF
Abstract: Imitation learning field requires expert data to train agents in a task. Most often, this learning approach suffers from the absence of avail- able data, which results in techniques being tested on its dataset. Creating datasets is a cumbersome process requiring researchers to train expert agents from scratch, record their interactions and test each benchmark method with newly created data. Moreover, creating new datasets for each new technique results in a lack of con- sistency in the evaluation process since each dataset can drastically vary in state and action distribution. In response, this work aims to address these issues by creating Imitation Learning Datasets, a toolkit that allows for: (i) curated expert policies with multithreaded support for faster dataset creation; (ii) readily available datasets and techniques with precise measurements; and (iii) sharing implementations of common imitation learning techniques.
BibTeX: @inproceedings{gavenski-luck-rodrigues:24, author = {N. Gavenski, M. Luck, O. Rodrigues}, title = {Imitation Learning Datasets: A Toolkit For Creating Datasets, Training Agents and Benchmarking}, booktitle = {Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems}, year = {2024}, url = {https://dl.acm.org/doi/10.5555/3635637.3663292}, doi = {https://doi.org/10.5555/3635637.3663292} }
2024	Montes, N., Luck, M., Osman, N., Rodrigues, O. and Sierra, C., Combining Theory of Mind and Abductive Reasoning in Agent-Oriented Programming, Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, DOI: 10.1007/s10458-023-09613-w, 2024. [Abstract] [BibTeX]	URL PDF
Abstract: In this paper we present TomAbd, a novel agent model extend- ing the BDI architecture with Theory of Mind capabilities, i.e. the capacity to adopt and reason from the perspective of others. By combining the Theory of Mind of TomAbd agents with abductive reasoning, agents can infer explanations for the behaviour of others, which they can incorporate into their own decision-making. We have implemented the TomAbd agent model and successfully tested its performance in the cooperative board game Hanabi.
BibTeX: @inproceedings{montes-et-al:24, author = {N. Montes, M. Luck, N. Osman, O. Rodrigues, C. Sierra}, title = {Combining Theory of Mind and Abductive Reasoning in Agent-Oriented Programming}, booktitle = {Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems}, year = {2024}, url = {https://link.springer.com/article/10.1007/s10458-023-09613-w}, doi = {https://doi.org/10.1007/s10458-023-09613-w} }
2023	Amaral, G., Rodrigues, O. and Simperl, E., ProVe: A Pipeline for Automated Provenance Verification of Knowledge Graphs against Textual Sources, The Semantic Web Journal, DOI: 10.3233/SW-233467, 2023. [Abstract] [BibTeX]	URL PDF
Abstract: Knowledge Graphs are repositories of information that gather data from a multitude of domains and sources in the form of semantic triples, serving as a source of structured data for various crucial applications in the modern web landscape, from Wikipedia infoboxes to search engines. Such graphs mainly serve as secondary sources of information and depend on well-documented and verifiable provenance to ensure their trustworthiness and usability. However, their ability to systematically assess and assure the quality of this provenance, most crucially whether it properly supports the graph's information, relies mainly on manual processes that do not scale with size. ProVe aims at remedying this, consisting of a pipelined approach that automatically verifies whether a Knowledge Graph triple is supported by text extracted from its documented provenance. ProVe is intended to assist information curators and consists of four main steps involving rule-based methods and machine learning models: text extraction, triple verbalisation, sentence selection, and claim verification. ProVe is evaluated on a Wikidata dataset, achieving promising results overall and excellent performance on the binary classification task of detecting support from provenance, with 87.5% accuracy and 82.9% F1-macro on text-rich sources. The evaluation data and scripts used in this paper are available on GitHub and Figshare.
BibTeX: @article{amaral-et-al:23, author = {Gabriel Amaral and Odinaldo Rodrigues and Elena Simperl}, title = {ProVe: A Pipeline for Automated Provenance Verification of Knowledge Graphs against Textual Sources}, journal = {The Semantic Web Journal}, year = {2023}, url = {http://doi.org/10.3233/SW-233467}, doi = {https://doi.org/10.3233/SW-233467} }
2023	Jorgensen, M., Waller, M., Cocarascu, O., Criado, N., Rodrigues, O., Such, J. and Black, E., Investigating the Legality of Bias Mitigation Methods in the United Kingdom, IEEE Technology and Society Magazine, Vol. 42 (4), pp. 87-94, DOI: 10.1109/MTS.2023.3341465, 2023. [Abstract] [BibTeX]	URL PDF
Abstract: Algorithmic Decision-Making Systems (ADMS) 1 fairness issues have been well highlighted over the past decade [1] , including some facial recognition systems struggling to identify people of color [2] . In 2021, Uber drivers filed a claim with the U.K. ’s employment tribunal for unfair dismissal resulting from automated facial recognition technology by Microsoft [3] . Bias mitigation methods have been developed to reduce discrimination from ADMS. These typically operationalize fairness notions as fairness metrics to minimize discrimination [4] . We refer to ADMS to which bias mitigation methods have been applied as “mitigated ADMS” or, in the singular, a “mitigated system.”
BibTeX: @article{Jorgensen2023, author = {Jorgensen, Mackenzie and Waller, Madeleine and Cocarascu, Oana and Criado, Natalia and Rodrigues, Odinaldo and Such, Jose and Black, Elizabeth}, title = {Investigating the Legality of Bias Mitigation Methods in the United Kingdom}, journal = {IEEE Technology and Society Magazine}, year = {2023}, volume = {42}, number = {4}, pages = {87-94}, doi = {https://doi.org/10.1109/MTS.2023.3341465} }
2023	Montes, N., Luck, M., Osman, N., Rodrigues, O. and Sierra, C., Combining Theory of Mind and Abductive Reasoning in Agent-Oriented Programming, Autonomous Agents and Multi-Agent Systems, DOI: 10.1007/s10458-023-09613-w, 2023. [Abstract] [BibTeX]	URL PDF
Abstract: This paper presents a novel model, called TomAbd, that endows autonomous agents with Theory of Mind capabilities. TomAbd agents are able to simulate the perspective of the world that their peers have and reason from their perspective. Furthermore, TomAbd agents can reason from the perspective of others down to an arbitrary level of recursion, using Theory of Mind of nth order. By combining the previous capability with abductive reasoning, TomAbd agents can infer the beliefs that others were relying upon to select their actions, hence putting them in a more informed position when it comes to their own decision-making. We have tested the TomAbd model in the challenging domain of Hanabi, a game characterised by cooperation and imperfect information. Our results show that the abilities granted by the TomAbd model boost the performance of the team along a variety of metrics, including final score, efficiency of communication, and uncertainty reduction.
BibTeX: @article{nieves-et-al:23, author = {Nieves Montes , Michael Luck , Nardine Osman, Odinaldo Rodrigues, Carles Sierra}, title = {Combining Theory of Mind and Abductive Reasoning in Agent-Oriented Programming}, journal = {Autonomous Agents and Multi-Agent Systems}, year = {2023}, url = {https://doi.org/10.1007/s10458-023-09613-w}, doi = {https://doi.org/10.1007/s10458-023-09613-w} }
2023	Rodrigues, O., Representing and Manipulating Large Sequences of Argumentation Labellings, The 38th ACM/SIGAPP Symposium on Applied Computing (SAC’23), DOI: 10.1145/3555776.3577756, 2023. [Abstract] [BibTeX]	URL PDF
Abstract: This paper proposes a canonical ordering of arguments within abstract argumentation labellings and two new types of efficient representations of these labellings for use in applications involving the computation of argumentation semantics. The space requirements of the representations are analysed, benchmarked on a class of hard enumeration problems taken from the International Competition on Computational Models of Argumentation (ICCMA), and compared for efficiency. We found that they both offer significant reductions of the memory representation requirements of large labellings, sometimes of up to 75%. We argue that the new way of looking at labellings provided by one of the representations, i.e., by considering repetitions of segment assignments within labellings, paves the way for investigations of new applications in argumentation theory.
BibTeX: @inbook{rodrigues-segements:23, author = {Odinaldo Rodrigues}, title = {Representing and Manipulating Large Sequences of Argumentation Labellings}, booktitle = {The 38th ACM/SIGAPP Symposium on Applied Computing (SAC’23)}, year = {2023}, doi = {https://doi.org/10.1145/3555776.3577756} }
2023	Waller, M., Cocarascu, O. and Rodrigues, O., A Survey of Bias Mitigation Methods for Binary Classification Decision-Making Systems, arXiv, DOI: 10.48550/arXiv.2305.20020, 2023. [Abstract] [BibTeX]	URL PDF
Abstract: Bias mitigation methods for binary classification decision-making systems have been widely researched due to the ever-growing importance of designing fair machine learning processes that are impartial and do not discriminate against individuals or groups based on protected personal characteristics. In this paper, we present a structured overview of the research landscape for bias mitigation methods, report on their benefits and limitations, and provide recommendations for the development of future bias mitigation methods for binary classification.
BibTeX: @article{waller:23a, author = {Madeleine Waller, Oana Cocarascu, Odinaldo Rodrigues}, title = {A Survey of Bias Mitigation Methods for Binary Classification Decision-Making Systems}, journal = {arXiv}, year = {2023}, url = {https://doi.org/10.48550/arXiv.2305.20020}, doi = {https://doi.org/10.48550/arXiv.2305.20020} }
2023	Waller, M., Rodrigues, O. and Cocarascu, O., Recommendations for Bias Mitigation Methods: Applicability and Legality, Proceedings of the 1st Workshop on Fairness and Bias in Artificial Intelligence, DOI: https://ceur-ws.org/Vol-3523/paper3.pdf, 2023. [Abstract] [BibTeX]	URL PDF
Abstract: With AI-based decision-making systems increasingly being deployed in various sectors, research on fairness in AI has become even more important. In this position paper, we highlight a number of significant practical applicability limitations and regulatory compliance issues associated with existing bias mitigation methods. These limitations indicate a pressing need for a change in the approach to their development. In order to address them, we provide a list of recommendations for new bias mitigation methods that are not only effective, but can also be applied in real-world scenarios and comply with legal requirements.
BibTeX: @inproceedings{waller-b:23, author = {Madeleine Waller, Odinaldo Rodrigues, Oana Cocarascu}, title = {Recommendations for Bias Mitigation Methods: Applicability and Legality}, booktitle = {Proceedings of the 1st Workshop on Fairness and Bias in Artificial Intelligence}, publisher = {CEUR Workshop Proceedings}, year = {2023}, url = {https://ceur-ws.org/Vol-3523/paper3.pdf}, doi = {https://ceur-ws.org/Vol-3523/paper3.pdf} }
2022	Amaral, G., Pinnis, M., Skadiņa, I., Rodrigues, O. and Simperl, E., Statistical and Neural Methods for Cross-lingual Entity Label Mapping in Knowledge Graphs, Text, Speech, and Dialogue, pp. 39-51, DOI: 10.1007/978-3-031-16270-1_4, 2022. [Abstract] [BibTeX]	URL PDF
Abstract: Knowledge bases such as Wikidata amass vast amounts of named entity information, such as multilingual labels, which can be extremely useful for various multilingual and cross-lingual applications. However, such labels are not guaranteed to match across languages from an information consistency standpoint, greatly compromising their usefulness for fields such as machine translation. In this work, we investigate the application of word and sentence alignment techniques coupled with a matching algorithm to align cross-lingual entity labels extracted from Wikidata in 10 languages. Our results indicate that mapping between Wikidata’s main labels stands to be considerably improved (up to 20 points in F1-score) by any of the employed methods. We show how methods relying on sentence embeddings outperform all others, even across different scripts. We believe the application of such techniques to measure the similarity of label pairs, coupled with a knowledge base rich in high-quality entity labels, to be an excellent asset to machine translation.
BibTeX: @incollection{Amaral_2022, author = {Gabriel Amaral and Mārcis Pinnis and Inguna Skadiņa and Odinaldo Rodrigues and Elena Simperl}, title = {Statistical and Neural Methods for Cross-lingual Entity Label Mapping in Knowledge Graphs}, booktitle = {Text, Speech, and Dialogue}, publisher = {Springer International Publishing}, year = {2022}, pages = {39--51}, doi = {https://doi.org/10.1007/978-3-031-16270-1_4} }
2022	Amaral, G., Rodrigues, O. and Simperl, E., WDV: A Broad Data Verbalisation Dataset Built from Wikidata, The Semantic Web textendash ISWC 2022, pp. 556-574, DOI: 10.1007/978-3-031-19433-7_32, 2022. [Abstract] [BibTeX]	URL PDF
Abstract: Data verbalisation is a task of great importance in the current field of natural language processing, as there is a clear benefit in the transformation of our abundant structured and semi-structured data into human-readable formats. Verbalising Knowledge Graph (KG) data focuses on converting interconnected triple-based claims, formed of subject, predicate, and object, into text. Although KG verbalisation datasets exist for some KGs, there are still limitations in their applicability to many scenarios. This is especially true for Wikidata, where available datasets either loosely couple claim sets with textual information or heavily focus on predicates around biographies, cities, and countries. To address these gaps, we propose WDV, a large KG claim verbalisation dataset built from Wikidata, with a tight coupling between triples and text, covering a wide variety of entities and predicates. We also evaluate the quality of our verbalisations through a reusable workflow for measuring human-centred fluency and adequacy scores. Our data (https://doi.org/10.6084/m9.figshare.17159045.v1) and code (https://github.com/gabrielmaia7/WDV) are openly available in the hopes of furthering research towards KG verbalisation.
BibTeX: @incollection{Amaral_WDV:22, author = {Gabriel Amaral and Odinaldo Rodrigues and Elena Simperl}, title = {WDV: A Broad Data Verbalisation Dataset Built from Wikidata}, booktitle = {The Semantic Web textendash ISWC 2022}, publisher = {Springer International Publishing}, year = {2022}, pages = {556--574}, doi = {https://doi.org/10.1007/978-3-031-19433-7_32} }
2022	Black, E., Brandão, M., Cocarascu, O., Keijzer, B.D., Du, Y., Long, D., Luck, M., McBurney, P., Meroño-Peñuela, A., Miles, S., Modgil, S., Moreau, L., Polukarov, M., Rodrigues, O. and Ventre, C., Reasoning and interaction for social artificial intelligence, AI Communications, Vol. 35 (4), pp. 309-325, DOI: 10.3233/aic-220133, 2022. [Abstract] [BibTeX]	URL PDF
Abstract: Current work on multi-agent systems at King’s College London is extensive, though largely based in two research groups within the Department of Informatics: the Distributed Artificial Intelligence (DAI) thematic group and the Reasoning & Planning (RAP) thematic group. DAI combines AI expertise with political and economic theories and data, to explore social and technological contexts of interacting intelligent entities. It develops computational models for analysing social, political and economic phenomena to improve the effectiveness and fairness of policies and regulations, and combines intelligent agent systems, software engineering, norms, trust and reputation, agent-based simulation, communication and provenance of data, knowledge engineering, crowd computing and semantic technologies, and algorithmic game theory and computational social choice, to address problems arising in autonomous systems, financial markets, privacy and security, urban living and health. RAP conducts research in symbolic models for reasoning involving argumentation, knowledge representation, planning, and other related areas, including development of logical models of argumentation-based reasoning and decision-making, and their usage for explainable AI and integration of machine and human reasoning, as well as combining planning and argumentation methodologies for strategic argumentation.
BibTeX: @article{Black_2022, author = {Elizabeth Black and Martim Brandão and Oana Cocarascu and Bart De Keijzer and Yali Du and Derek Long and Michael Luck and Peter McBurney and Albert Meroño-Peñuela and Simon Miles and Sanjay Modgil and Luc Moreau and Maria Polukarov and Odinaldo Rodrigues and Carmine Ventre}, title = {Reasoning and interaction for social artificial intelligence}, journal = {AI Communications}, publisher = {IOS Press}, year = {2022}, volume = {35}, number = {4}, pages = {309--325}, doi = {https://doi.org/10.3233/aic-220133} }
2022	Pober, J., Luck, M. and Rodrigues, O., From Subsymbolic to Symbolic: A Blueprint for Investigation, CEUR Workshop Proceedings, DOI: https://ceur-ws.org/Vol-3212/, 2022. [Abstract] [BibTeX]	URL PDF
Abstract: In this paper, we sketch a framework for integration between subsymbolic and symbolic representations,consisting of a series of layers and mappings between elements across the layers. Each layer corresponds toa particular level of abstraction about phenomena in the environment being observed in the layers below.Through an iterative process, the differences between the elements in successive iterations within a givenlayer are captured as transformations between the elements and used for identification and recognition ofobjects as well as prediction and verification of the environment in future iterations. A bridge between thesubsymbolic and symbolic levels can be built by successively adding layers at ever more sophisticated levelsof abstraction. This approach aims to benefit from subsymbolic learning, while harnessing the abstractionand reasoning powers of classical symbolic AI techniques.
BibTeX: @inbook{Pober2022, author = {Joseph Pober and Michael Luck and Odinaldo Rodrigues}, title = {From Subsymbolic to Symbolic: A Blueprint for Investigation}, booktitle = {CEUR Workshop Proceedings}, year = {2022}, url = {https://ceur-ws.org/Vol-3212/}, doi = {https://ceur-ws.org/Vol-3212/} }
2021	Amaral, G., Piscopo, A., Kaffee, L.-a., Rodrigues, O. and Simperl, E., Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach, J. Data and Information Quality, Vol. 13 (4), DOI: 10.1145/3484828, 2021. [Abstract] [BibTeX]	URL PDF
Abstract: Wikidata is one of the most important sources of structured data on the web, built by a worldwide community of volunteers. As a secondary source, its contents must be backed by credible references; this is particularly important, as Wikidata explicitly encourages editors to add claims for which there is no broad consensus, as long as they are corroborated by references. Nevertheless, despite this essential link between content and references, Wikidata's ability to systematically assess and assure the quality of its references remains limited. To this end, we carry out a mixed-methods study to determine the relevance, ease of access, and authoritativeness of Wikidata references, at scale and in different languages, using online crowdsourcing, descriptive statistics, and machine learning. Building on previous work of ours, we run a series of microtasks experiments to evaluate a large corpus of references, sampled from Wikidata triples with labels in several languages. We use a consolidated, curated version of the crowdsourced assessments to train several machine learning models to scale up the analysis to the whole of Wikidata. The findings help us ascertain the quality of references in Wikidata and identify common challenges in defining and capturing the quality of user-generated multilingual structured data on the web. We also discuss ongoing editorial practices, which could encourage the use of higher-quality references in a more immediate way. All data and code used in the study are available on GitHub for feedback and further improvement and deployment by the research community.
BibTeX: @article{Amaral2021, author = {Amaral, Gabriel and Piscopo, Alessandro and Kaffee, Lucie-aimée and Rodrigues, Odinaldo and Simperl, Elena}, title = {Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach}, journal = {J. Data and Information Quality}, publisher = {Association for Computing Machinery}, year = {2021}, volume = {13}, number = {4}, url = {https://doi.org/10.1145/3484828}, doi = {https://doi.org/10.1145/3484828} }
2020	Baumann, R., Gabbay, D.M. and Rodrigues, O., Forgetting an argument, Proceedings of the 34th Conference on Artificial Intelligence, DOI: https://doi.org/10.1609/aaai.v34i03.5662, 2020. [Abstract] [BibTeX]	URL PDF
Abstract: The notion of forgetting, as considered in the famous paper by Lin and Reiter has been extensively studied in classical logic and more recently, in non-monotonic formalisms like logic programming. In this paper, we convey the idea of forgetting to another major AI formalism, namely Dung-style argumentation frameworks. Our approach is axiomatic-driven and not limited to any specific semantics: we propose semantical and syntactical desiderata encoding different criteria for what forgetting an argument might mean; analyze how these criteria relate to each other; and check whether the criteria can be satisfied in general. The analysis is done for a number of widely used argumentation semantics. Our investigation shows that almost all desiderata are individually satisfiable. However, combinations of semantical and/or syntactical conditions reveal a much more interesting landscape. For instance, we found that the ad hoc approach to forgetting an argument, i.e., by the syntactical removal of the argument and all of its associated attacks, is too restrictive and only compatible with the two weakest semantical desiderata. Amongst the several interesting combinations identified, we showed that one satisfies a notion of minimal change and presented an algorithm that given an AF F and argument x, constructs a suitable AF G satisfying the conditions in the combination.
BibTeX: @inproceedings{baumann-gabbay-rodrigues:20, author = {R. Baumann, D. M. Gabbay, O. Rodrigues}, title = {Forgetting an argument}, booktitle = {Proceedings of the 34th Conference on Artificial Intelligence}, year = {2020}, doi = {https://doi.org/10.1609/aaai.v34i03.5662} }
2019	Rodrigues, O., Representing and Comparing Large Sets of Extensions of Abstract Argumentation Frameworks, Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (SAC'19), DOI: 10.1145/3297280.3297394, 2019. [Abstract] [BibTeX]	URL PDF
Abstract: In argumentation theory, some reasoning problems involve the enu- meration of all extensions of an abstract argumentation framework. Abstractly speaking, extensions are simply subsets of a given do- main having some special properties. The result of the enumeration is usually presented as a single text file with elements and sets sepa- rated by designated delimiters. Neither the elements within each set (a single extension), nor the extensions themselves are presented in any pre-defined order. Events such as the International Competition of Computational Models of Argumentation require the compar- ison of a large number of enumerations and thus performing the comparisons very efficiently has become very desirable. This paper presents and compares three different alternative representations of extensions, one of which is novel for the argumentation domain, and provides an empirical evaluation of their effectiveness in the comparison of large enumerations. We found that the newly pro- posed representation can perform the comparisons in a much more memory and time efficient manner than existing solutions.
BibTeX: @inproceedings{rodrigues-mpz:19, author = {O. Rodrigues}, title = {Representing and Comparing Large Sets of Extensions of Abstract Argumentation Frameworks}, booktitle = {Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (SAC'19)}, year = {2019}, doi = {https://doi.org/10.1145/3297280.3297394} }
2019	Hao, Q., Keppens, J. and Rodrigues, O., A Self-Training Ontology-Driven Approach to Topic Classification, The 12th International Conference on Computer Science and Information Technology, 2019. [Abstract] [BibTeX]	PDF
Abstract: Abstract-Latent Dirichlet Allocation (LDA) is a topic classification technique that produces a probabilistic model based on word co-occurrence, for the purpose of text classification. Conventional LDA ignores the fact that words may have multiple meanings and that different words may have the same meaning. This focus on the words rather than their meanings limits the accuracy of the classification. This work introduces an intermediate labelling component to LDA using the concepts in DBpedia’s ontology to help capture some of the possible meanings of the words appearing in the documents. We call this novel technique Ontology-Driven LDA (OLDA). As for LDA, OLDA can be combined with a self-training procedure to reduce the amount of manually classified data required (we refer to the self- training variant as ST-OLDA). We compared the classification performance of ST-OLDA against the performance of two other leading self-training classification methods: ST Term Frequency- Inverse Document Frequency (ST TF-IDF) and ST-LDA. Our experimental results show that the inclusion of the ontology component helps to reduce the training time by nearly half whilst achieving the highest accuracy in the classification of four widely used datasets. In particular, ST-OLDA outperforms ST-LDA’s accuracy of classification by as much as 11%.
BibTeX: @inproceedings{st-olda:2019, author = {Q. Hao and J. Keppens and O. Rodrigues}, title = {A Self-Training Ontology-Driven Approach to Topic Classification}, booktitle = {The 12th International Conference on Computer Science and Information Technology}, year = {2019} }
2018	Rodrigues, O., EqArgSolver -- System Description, Proceedings of the 4th Intl. Conference on Theory and Applications of Formal Argumentation, pp. 150-158, DOI: 10.1007/978-3-319-75553-3_11, 2018. [BibTeX]	URL PDF
BibTeX: @inproceedings{eqargsolver:17, author = {Odinaldo Rodrigues}, title = {EqArgSolver -- System Description}, booktitle = {Proceedings of the 4th Intl. Conference on Theory and Applications of Formal Argumentation}, year = {2018}, pages = {150-158}, doi = {https://doi.org/10.1007/978-3-319-75553-3_11} }
2018	Rodrigues, O., A Forward Propagation Algorithm for the Computation of the Semantics of Argumentation Frameworks, Theory and Applications of Formal Argumentation, pp. 120-136, DOI: 10.1007/978-3-319-75553-3_8, 2018. [BibTeX]	URL PDF
BibTeX: @incollection{Rodrigues_2018, author = {Odinaldo Rodrigues}, title = {A Forward Propagation Algorithm for the Computation of the Semantics of Argumentation Frameworks}, booktitle = {Theory and Applications of Formal Argumentation}, publisher = {Springer International Publishing}, year = {2018}, pages = {120--136}, doi = {https://doi.org/10.1007/978-3-319-75553-3_8} }
2018	Rodrigues, O., Black, E., Luck, M. and Murphy, J., On structural properties of argumentation frameworks: Lessons from ICCMA, CEUR Workshop Proceedings, Vol. 2171, pp. 22-35, 2018. [Abstract] [BibTeX]	PDF
Abstract: It is well known that the computation of solutions to decision and enumeration problems in argumentation can be very hard. In this work, we analyse some of the results of the 2017 International Competition on Computational Models of Argumentation. Our analysis shifts the focus from the performance of individual solvers to how well/badly they can collectively tackle different classes of abstract argumentation frameworks. In so doing, we were able to identify the instances that were particularly difficult for all/most solvers and look into their particular structural properties.
BibTeX: @inproceedings{Rodrigues2018OnSP, author = {O. Rodrigues and E. Black and M. Luck and J. Murphy}, title = {On structural properties of argumentation frameworks: Lessons from ICCMA}, journal = {CEUR Workshop Proceedings}, publisher = {CEUR-WS}, year = {2018}, volume = {2171}, pages = {22--35}, note = {2nd International Workshop on Systems and Algorithms for Formal Argumentation, SAFA 2018 ; Conference date: 11-09-2018}, url = {https://ceur-ws.org/Vol-2171/paper_3.pdf} }
2018	Rodrigues, O., An Investigation into Reduction and Direct Approaches to the Computation of Argumentation Semantics, Logic, Intelligence and Artifices: Tributes to Tarcision H. C. Pequeno, pp. 97-120, 2018. [Abstract] [BibTeX]	PDF
Abstract: This paper compares the performance of the forward propagation algorithm proposed in [15] (which is used in the solver EqArgSolver) with two custom-built SAT-based argumentation solvers in the search for preferred extensions of abstract argumentation frameworks. The SAT-based solvers employ standard ways of computing argumentation semantics via the characterisation of the concept of extensions as models of propositional logic theories. As a result, the comparisons offer new insights about the employment and combination of reduction and direct approaches to the computation of argumentation semantics.
BibTeX: @incollection{rodrigues-RD:17, author = {O. Rodrigues}, title = {An Investigation into Reduction and Direct Approaches to the Computation of Argumentation Semantics}, booktitle = {Logic, Intelligence and Artifices: Tributes to Tarcision H. C. Pequeno}, publisher = {College Publications}, year = {2018}, pages = {97-120}, url = {https://www.collegepublications.co.uk/tributes/?00038} }
2018	Young, A.P., Modgil, S. and Rodrigues, O., On the Interaction between Logic and Preference in Structured Argumentation, Theory and Applications of Formal Argumentation, pp. 35-50, DOI: 10.1007/978-3-319-75553-3_3, 2018. [BibTeX]	URL PDF
BibTeX: @inproceedings{young-et-al-tafa:17, author = {Anthony P. Young and Sanjay Modgil and Odinaldo Rodrigues}, title = {On the Interaction between Logic and Preference in Structured Argumentation}, booktitle = {Theory and Applications of Formal Argumentation}, publisher = {Springer International Publishing}, year = {2018}, pages = {35--50}, doi = {https://doi.org/10.1007/978-3-319-75553-3_3} }
2017	Hao, Q., Keppens, J. and Rodrigues, O., A Verb-based Algorithm for Multiple-Relation Extraction from Single Sentences, Proceedings of the 16th International Conference on Information and Knowledge Engineering, 2017. [Abstract] [BibTeX]	PDF
Abstract: With the growing number of unstructured articles written in natural-language, automated extraction of knowledge, such as associations between entities, is becoming essential for many applications. In this paper, we develop an automated verb-based algorithm for multiple relation extraction from unstructured data obtained on-line. Named Entity Recognition (NER) techniques were applied to extract biomedical entities and relations were recognized by algorithms with Natural Language Processing (NLP) techniques. Evaluation based on F-measure with a random sample of sentences from biomedical literature results an average precision of 90% and recall of 82%. We also compared the performance of the proposed algorithm with a single-relation extraction algorithm, indicating improvements of this work. In conclusion, the preliminary study indicates that this method for multiple-relation extraction from unstructured literature is effective. With different training dataset, the algorithm can be applied to different domains. The automated method can be applied to detect and predict hidden relationships among varying areas.
BibTeX: @inproceedings{hao-et-al:17, author = {Qi Hao and Jeroen Keppens and Odinaldo Rodrigues}, title = {A Verb-based Algorithm for Multiple-Relation Extraction from Single Sentences}, booktitle = {Proceedings of the 16th International Conference on Information and Knowledge Engineering}, year = {2017}, url = {https://csce.ucmss.com/cr/books/2017/LFS/CSREA2017/IKE3227.pdf} }
2016	Gabbay, D.M. and Rodrigues, O., Introducing Bayesian Argumentation Networks, The IfColog Journal of Logics and their Applications, Vol. 3 (2), pp. 241-278, 2016. [BibTeX]	PDF
BibTeX: @article{bayes-argum-network:16, author = {D. M. Gabbay and O. Rodrigues}, title = {Introducing Bayesian Argumentation Networks}, journal = {The IfColog Journal of Logics and their Applications}, publisher = {College Publications}, year = {2016}, volume = {3}, number = {2}, pages = {241-278} }
2016	Gabbay, D. and Rodrigues, O., Degrees of “in”, “out” and “undecided” in Argumentation Networks, Vol. 287, Frontiers in Artificial Intelligence and Applications, pp. 319-326, DOI: 10.3233/978-1-61499-686-6-319, 2016. [BibTeX]	URL PDF
BibTeX: @inproceedings{gabbay-rodrigues:16c, author = {D. Gabbay and O. Rodrigues}, title = {Degrees of “in”, “out” and “undecided” in Argumentation Networks}, booktitle = {Frontiers in Artificial Intelligence and Applications}, year = {2016}, volume = {287}, pages = {319-326}, doi = {https://doi.org/10.3233/978-1-61499-686-6-319} }
2016	Gabbay, D.M. and Rodrigues, O., Further Applications of the Gabbay-Rodrigues Iteration Schema in Argumentation and Revision Theories, Vol. 29, Computational Models of Rationality, pp. 392-407, 2016. [BibTeX]	PDF
BibTeX: @incollection{gabbay-rodrigues-GKI:16, author = {D. M. Gabbay and O. Rodrigues}, title = {Further Applications of the Gabbay-Rodrigues Iteration Schema in Argumentation and Revision Theories}, booktitle = {Computational Models of Rationality}, publisher = {College Publications}, year = {2016}, volume = {29}, pages = {392-407}, url = {https://www.collegepublications.co.uk/tributes/?00029} }
2016	Hosseini, S.A., Modgil, S. and Rodrigues, O., Estimating Second-Order Arguments in Dialogical Settings, Proceedings of the 2016 International Conference on Autonomous Agents and Multiagents Systems, pp. 1469-1470, 2016. [BibTeX]	PDF
BibTeX: @inproceedings{hosseini-modgil-rodrigues:16, author = {S. A. Hosseini and S. Modgil and O. Rodrigues}, title = {Estimating Second-Order Arguments in Dialogical Settings}, booktitle = {Proceedings of the 2016 International Conference on Autonomous Agents and Multiagents Systems}, publisher = {International Foundation for Autonomous Agents and Multiagent Systems}, year = {2016}, pages = {1469-1470} }
2016	Hosseini, S.A., Modgil, S. and Rodrigues, O., Assigning Likelihoods to Interlocutors' Beliefs and Arguments, Vol. 287, Frontiers in Artificial Intelligence and Applications, pp. 339-350, DOI: 10.3233/978-1-61499-686-6-339, 2016. [BibTeX]	URL PDF
BibTeX: @inproceedings{hosseini-modgil-rodrigues:16d, author = {S. A Hosseini and S. Modgil and O. Rodrigues}, title = {Assigning Likelihoods to Interlocutors' Beliefs and Arguments}, booktitle = {Frontiers in Artificial Intelligence and Applications}, year = {2016}, volume = {287}, pages = {339-350}, doi = {https://doi.org/10.3233/978-1-61499-686-6-339} }
2016	Rodrigues, O., Introducing EqArgSolver: An argumentation solver using equational semantics, 2016. [BibTeX]	PDF
BibTeX: @misc{rodrigues:16e, author = {O. Rodrigues}, title = {Introducing EqArgSolver: An argumentation solver using equational semantics}, year = {2016}, note = {The First International Workshop on Systems and Algorithms for Formal Argumentation, colocated with COMMA 2016} }
2016	Young, A., Modgil, S. and Rodrigues, O., Prioritised Default Logic as Rational Argumentation, Proceedings of the 2016 International Conference on Autonomous Agents and Multiagents Systems, pp. 626-634, DOI: 10.5555/2936924.2937018, 2016. [BibTeX]	URL PDF
BibTeX: @inproceedings{young-modgil-rodrigues:16, author = {A. Young and S. Modgil and O. Rodrigues}, title = {Prioritised Default Logic as Rational Argumentation}, booktitle = {Proceedings of the 2016 International Conference on Autonomous Agents and Multiagents Systems}, publisher = {International Foundation for Autonomous Agents and Multiagent Systems}, year = {2016}, pages = {626-634}, url = {http://dl.acm.org/citation.cfm?id=2936924.2937018}, doi = {https://doi.org/10.5555/2936924.2937018} }
2015	Gabbay, D.M. and Rodrigues, O., Equilibrium States in Numerical Argumentation Networks, Logica Universalis, pp. 1-63, DOI: 10.1007/s11787-015-0119-7, 2015. [BibTeX]	URL PDF
BibTeX: @article{esnan-15, author = {Gabbay, D. M. and Rodrigues, O.}, title = {Equilibrium States in Numerical Argumentation Networks}, journal = {Logica Universalis}, publisher = {Springer Basel}, year = {2015}, pages = {1-63}, url = {http://dx.doi.org/10.1007/s11787-015-0119-7}, doi = {https://doi.org/10.1007/s11787-015-0119-7} }
2015	Meneguzzi, F., Rodrigues, O., Oren, N., Vasconcelos, W.W. and Luck, M., BDI reasoning with normative considerations, Engineering Applications of Artificial Intelligence, Vol. 43 (0), pp. 127 - 146, DOI: http://dx.doi.org/10.1016/j.engappai.2015.04.011, 2015. [BibTeX]	URL PDF
BibTeX: @article{Meneguzzi2015127, author = {F. Meneguzzi and O. Rodrigues and N. Oren and W. W. Vasconcelos and M. Luck}, title = {BDI reasoning with normative considerations}, journal = {Engineering Applications of Artificial Intelligence}, year = {2015}, volume = {43}, number = {0}, pages = {127 - 146}, url = {http://www.sciencedirect.com/science/article/pii/S0952197615000925}, doi = {https://doi.org/10.1016/j.engappai.2015.04.011} }
2015	Gabbay, D.M. and Rodrigues, O., Probabilistic Argumentation: An Equational Approach., Logica Universalis, Vol. 9 (3), pp. 345-382, DOI: 10.1007/s11787-015-0120-1, 2015. [BibTeX]	URL PDF
BibTeX: @article{prob-argum:15, author = {D. M. Gabbay and O. Rodrigues}, title = {Probabilistic Argumentation: An Equational Approach.}, journal = {Logica Universalis}, year = {2015}, volume = {9}, number = {3}, pages = {345-382}, doi = {https://doi.org/10.1007/s11787-015-0120-1} }
2015	Rodrigues, O., GRIS: Computing traditional argumentation semantics through numerical iterations, 2015. [BibTeX]
BibTeX: @inproceedings{Rodrigues2015GRISCT, author = {O. Rodrigues}, title = {GRIS: Computing traditional argumentation semantics through numerical iterations}, year = {2015}, url = {https://api.semanticscholar.org/CorpusID:17064520} }
2014	Gabbay, D.M. and Rodrigues, O., A self-correcting iteration schema for argumentation networks, Proceedings of COMMA V, pp. 377 - 384, DOI: 10.3233/978-1-61499-436-7-377, 2014. [BibTeX]	URL PDF
BibTeX: @inproceedings{gabbay-rodrigues:COMMA2014, author = {D. M. Gabbay and O. Rodrigues}, title = {A self-correcting iteration schema for argumentation networks}, booktitle = {Proceedings of COMMA V}, publisher = {IOS Press}, year = {2014}, pages = {377 - 384}, doi = {https://doi.org/10.3233/978-1-61499-436-7-377} }
2014	Gabbay, D.M. and Rodrigues, O., An Equational Approach to the Merging of Argumentation Networks, Journal of Logic and Computation, Vol. 24, pp. 1253-1277, DOI: 10.1007/978-3-642-32897-8_14, 2014. [BibTeX]	URL PDF
BibTeX: @article{gabbay-rodrigues-jlc:13, author = {D. M. Gabbay and O. Rodrigues}, title = {An Equational Approach to the Merging of Argumentation Networks}, journal = {Journal of Logic and Computation}, publisher = {OUP}, year = {2014}, volume = {24}, pages = {1253-1277}, doi = {https://doi.org/10.1007/978-3-642-32897-8_14} }
2014	Hosseini, S.A., Modgil, S. and Rodrigues, O., Enthymeme Construction in Dialogues using Shared Knowledge, Proceedings of COMMA V, pp. 325-332, DOI: 10.3233/978-1-61499-436-7-325, 2014. [BibTeX]	URL PDF
BibTeX: @inproceedings{hosseini-modgil-rodrigues:COMMA2014, author = {S. A. Hosseini and S. Modgil and O. Rodrigues}, title = {Enthymeme Construction in Dialogues using Shared Knowledge}, booktitle = {Proceedings of COMMA V}, publisher = {IOS Press}, year = {2014}, pages = {325-332}, doi = {https://doi.org/10.3233/978-1-61499-436-7-325} }
2012	Gabbay, D.M. and Rodrigues, O., A Numerical Approach to the Merging of Argumentation Networks, Proceedings of CLIMA XIII, pp. 195-212, DOI: 10.1007/978-3-642-32897-8_14, 2012. [BibTeX]	URL PDF
BibTeX: @inproceedings{gabbay-rodrigues:12, author = {D. M. Gabbay and O. Rodrigues}, title = {A Numerical Approach to the Merging of Argumentation Networks}, booktitle = {Proceedings of CLIMA XIII}, publisher = {Springer-Verlag}, year = {2012}, pages = {195-212}, doi = {https://doi.org/10.1007/978-3-642-32897-8_14} }
2011	Rodrigues, O., Gabbay, D. and Russo, A., Belief Revision, Handbook of Philosophical Logic: Volume 16, pp. 1-114, DOI: 10.1007/978-94-007-0479-4_1, 2011. [BibTeX]	URL
BibTeX: @incollection{Rodrigues:2011, author = {Odinaldo Rodrigues and Dov Gabbay and Alessandra Russo}, title = {Belief Revision}, booktitle = {Handbook of Philosophical Logic: Volume 16}, publisher = {Springer Netherlands}, year = {2011}, pages = {1--114}, url = {https://doi.org/10.1007/978-94-007-0479-4_1}, doi = {https://doi.org/10.1007/978-94-007-0479-4_1} }
2010	Gabbay, D., Rodrigues, O. and Russo, A., Revision, Acceptability and Context: Theoretic and Algorithmic Aspects, pp. 386, DOI: 10.1007/978-3-642-14159-1, 2010. [BibTeX]	URL
BibTeX: @book{rac:2010, author = {Gabbay, D and Rodrigues, O and Russo, A}, title = {Revision, Acceptability and Context: Theoretic and Algorithmic Aspects}, publisher = {Springer Verlag}, year = {2010}, pages = {386}, url = {http://dx.doi.org/10.1007/978-3-642-14159-1}, doi = {https://doi.org/10.1007/978-3-642-14159-1} }
2008	Rodrigues, O., Gabbay, D.M. and Russo, A., Belief Revision in Non-Classical Logics, Review of Symbolic Logic, Vol. 1, pp. 267-304, DOI: 10.1017/S1755020308080246, 2008. [BibTeX]	URL
BibTeX: @article{non-classical-2, author = {O. Rodrigues and D. M. Gabbay and A. Russo}, title = {Belief Revision in Non-Classical Logics}, journal = {Review of Symbolic Logic}, year = {2008}, volume = {1}, pages = {267-304}, doi = {https://doi.org/10.1017/S1755020308080246} }
2006	Elsenbroich, C., Gabbay, D.M. and Rodrigues, O., Getting possibilities from the impossible, Proceedings of NMR-06, pp. 505-513, 2006. [BibTeX]
BibTeX: @inproceedings{elsenbroich-gabbay-rodrigues06, author = {C. Elsenbroich and D. M. Gabbay and O. Rodrigues}, title = {Getting possibilities from the impossible}, booktitle = {Proceedings of NMR-06}, publisher = {Institut fur Informatik}, year = {2006}, pages = {505-513}, note = {ISSN 1860-8477} }
2006	Gabbay, D.M., Pigozzi, G. and Rodrigues, O., Belief revision, belief merging and voting, Proceedings of the Seventh Conference on Logic and the Foundations of Games and Decision Theory (LOFT06), pp. 71-78, 2006. [BibTeX]
BibTeX: @inproceedings{Gabbay2006, author = {D. M. Gabbay and G. Pigozzi and O. Rodrigues}, title = {Belief revision, belief merging and voting}, booktitle = {Proceedings of the Seventh Conference on Logic and the Foundations of Games and Decision Theory (LOFT06)}, publisher = {University of Liverpool}, year = {2006}, pages = {71-78} }
2005	Rodrigues, O., Iterated Revision and Automatic Similarity Generation, Vol. 2, We will show them! Essays in honour of D. M. Gabbay, pp. 591-613, 2005. [Abstract] [BibTeX]
Abstract: In [Boutilier, 1996], Boutilier proposed a framework in which given a belief set K and a similarity ordering ≤ for K, the similarity ordering ≤ for K◦A based on ≤ could be automatically generated. As a by-product, a simple scheme for iteration of the revision process emerged. The scheme suffers however from some drawbacks. In this work we revisit the problem by considering an alternative way of bringing the epistemic similarity ordering ≤ for K up to date with respect to a sequence of revision operations. Our idea is to derive a similarity ordering for the sequence of revisions as a whole based on the individual similarity orderings of each sentence in the sequence.
BibTeX: @inbook{Rodrigues2005, author = {O. Rodrigues}, title = {Iterated Revision and Automatic Similarity Generation}, booktitle = {We will show them! Essays in honour of D. M. Gabbay}, publisher = {College Publications}, year = {2005}, volume = {2}, pages = {591-613} }
2004	Gabbay, D.M., Rodrigues, O. and Woods, J., Deletion in Resource Unbounded Logics - Belief Contraction, Anti-Formulae and Resource Overdraft: Part II, Vol. 1, Logic, Epistemology and the Unity of Science, pp. 291-326, 2004. [BibTeX]
BibTeX: @incollection{gabbay-rodrigues-woods04, author = {D. M. Gabbay and O. Rodrigues and J. Woods}, title = {Deletion in Resource Unbounded Logics - Belief Contraction, Anti-Formulae and Resource Overdraft: Part II}, booktitle = {Logic, Epistemology and the Unity of Science}, publisher = {Kluwer Academic Publishers}, year = {2004}, volume = {1}, pages = {291-326} }
2004	Rodrigues, O., d'Avila Garcez, A. and Russo, A., Reasoning about Requirements Evolution Using Clustered Belief Revision, Advances in Artificial Intelligence, Proceedings of 17th SBIA, pp. 41-51, 2004. [BibTeX]
BibTeX: @inproceedings{se:sbia, author = {O. Rodrigues and A. d'Avila Garcez and A. Russo}, title = {Reasoning about Requirements Evolution Using Clustered Belief Revision}, booktitle = {Advances in Artificial Intelligence, Proceedings of 17th SBIA}, publisher = {Springer-Verlag Berlin Heidelberg}, year = {2004}, pages = {41-51}, note = {LNAI 3171} }
2003	Rodrigues, O., Structured Clusters: A Framework to Reason with Contradictory Interests, Journal of Logic and Computation, Vol. 13 (1), pp. 69-97, 2003. [BibTeX]
BibTeX: @article{clusters, author = {O. Rodrigues}, title = {Structured Clusters: A Framework to Reason with Contradictory Interests}, journal = {Journal of Logic and Computation}, year = {2003}, volume = {13}, number = {1}, pages = {69-97} }
2003	Rodrigues, O., d'Avila Garcez, A. and Russo, A., Reasoning about Requirements Evolution Using Clustered Belief Revision, Proceedings of ACM ESEC/FSE International Workshop on Intelligent Technologies for Software Engineering WITSE03, 2003. [BibTeX]
BibTeX: @inproceedings{rodrigues-garcez-russo03, author = {O. Rodrigues and A. d'Avila Garcez and A. Russo}, title = {Reasoning about Requirements Evolution Using Clustered Belief Revision}, booktitle = {Proceedings of ACM ESEC/FSE International Workshop on Intelligent Technologies for Software Engineering WITSE03}, year = {2003} }
2002	Gabbay, D.M., Rodrigues, O. and Woods, J., Belief Contraction, Anti-Formulae and Resource Overdraft: Part I - Deletion in Resource Bounded Logics, Logic Journal of the IGPL, Vol. 10 (6), pp. 601-652, 2002. [BibTeX]
BibTeX: @article{gabbay-rodrigues-woods02, author = {D. M. Gabbay and O. Rodrigues and J. Woods}, title = {Belief Contraction, Anti-Formulae and Resource Overdraft: Part I - Deletion in Resource Bounded Logics}, journal = {Logic Journal of the IGPL}, year = {2002}, volume = {10}, number = {6}, pages = {601-652} }
2000	Gabbay, D.M., Rodrigues, O. and Russo, A., Revision by Translation, Information, Uncertainty and Fusion, pp. 3-31, DOI: 10.1007/978-1-4615-5209-3_1, 2000. [BibTeX]	URL
BibTeX: @inbook{revision-by-translation:00, author = {D. M. Gabbay and O. Rodrigues and A. Russo}, title = {Revision by Translation}, booktitle = {Information, Uncertainty and Fusion}, publisher = {Springer US}, year = {2000}, pages = {3--31}, url = {https://doi.org/10.1007/978-1-4615-5209-3_1}, doi = {https://doi.org/10.1007/978-1-4615-5209-3_1} }
1998	Rodrigues, O., A methodology for iterated information changeSchool: Department of Computing, Imperial College, 1998. [BibTeX]	PDF
BibTeX: @phdthesis{rodrigues98, author = {O. Rodrigues}, title = {A methodology for iterated information change}, school = {Department of Computing, Imperial College}, year = {1998} }
1997	Gabbay, D.M. and Rodrigues, O., Structured Belief Bases: a practical approach to prioritised base revision, Proceedings of First Internation Joint Conference on Qualitative and Quantitative Practical Reasoning, pp. 267-281, 1997. [BibTeX]
BibTeX: @inproceedings{gabbay-rodr:97-a, author = {D. M. Gabbay and O. Rodrigues}, title = {Structured Belief Bases: a practical approach to prioritised base revision}, booktitle = {Proceedings of First Internation Joint Conference on Qualitative and Quantitative Practical Reasoning}, publisher = {Springer-Verlag}, year = {1997}, pages = {267-281} }
1996	Gabbay, D.M. and Rodrigues, O., A methodology for iterated Theory Change, Practical Reasoning - First International Conference on Formal and Applied Practical Reasoning, FAPR'96, 1996. [BibTeX]
BibTeX: @inproceedings{gabbay-rodr:96-a, author = {D. M. Gabbay and O. Rodrigues}, title = {A methodology for iterated Theory Change}, booktitle = {Practical Reasoning - First International Conference on Formal and Applied Practical Reasoning, FAPR'96}, publisher = {Springer Verlag}, year = {1996} }
1996	Gabbay, D.M. and Rodrigues, O., Structured Databases: a framework to reason about Belief Change, Proceedings of the Theory and Formal Methods 1996 workshop, 1996. [BibTeX]
BibTeX: @inproceedings{gabbay-rodrigues96-b, author = {D. M. Gabbay and O. Rodrigues}, title = {Structured Databases: a framework to reason about Belief Change}, booktitle = {Proceedings of the Theory and Formal Methods 1996 workshop}, publisher = {Imperial College Press}, year = {1996} }
1996	Rodrigues, O., Ryan, M. and Schobbens, P.-Y., Counterfactuals and updates as inverse modalities, 6th Conference on Theoretical Aspects of Rationality and Knowledge, pp. 163-174, 1996. [BibTeX]
BibTeX: @inproceedings{rodr-ryan-schob:96, author = {O. Rodrigues and M. Ryan and P.-Y. Schobbens}, title = {Counterfactuals and updates as inverse modalities}, booktitle = {6th Conference on Theoretical Aspects of Rationality and Knowledge}, year = {1996}, pages = {163-174} }
1994	Rodrigues, O. and Benevides, M., PROMAL — Programming in modal action logic, Vol. 844, Programming Language Implementation and Logic Programming, pp. 457-458, DOI: 10.1007/3-540-58402-1_36, 1994. [BibTeX]	URL
BibTeX: @incollection{promal:94, author = {Rodrigues, Odinaldo and Benevides, Mario}, title = {PROMAL — Programming in modal action logic}, booktitle = {Programming Language Implementation and Logic Programming}, publisher = {Springer Berlin Heidelberg}, year = {1994}, volume = {844}, pages = {457-458}, url = {http://dx.doi.org/10.1007/3-540-58402-1_36}, doi = {https://doi.org/10.1007/3-540-58402-1_36} }
1994	Rodrigues, O. and Benevides, M.R.F., Belief Revision in Pseudo-Definite Sets, Proceedings of the 11th Brazilian Symposium on Artificial Intelligence (SBIA '94), 1994. [BibTeX]
BibTeX: @inproceedings{rodrigues-benevides94, author = {O. Rodrigues and M. R. F. Benevides}, title = {Belief Revision in Pseudo-Definite Sets}, booktitle = {Proceedings of the 11th Brazilian Symposium on Artificial Intelligence (SBIA '94)}, year = {1994} }
1993	Rodrigues, O., Prolog Modal de Ação e Revisão de Crenças em Conjuntos DefinidosSchool: COPPE - Universidade Federal do Rio de Janeiro - Brazil, 1993. [BibTeX]
BibTeX: @mastersthesis{rodrigues93, author = {O. Rodrigues}, title = {Prolog Modal de Ação e Revisão de Crenças em Conjuntos Definidos}, school = {COPPE - Universidade Federal do Rio de Janeiro - Brazil}, year = {1993}, note = {Published in the Federal University of Rio de Janeiro, Brazil} }
1993	Rodrigues, O. and Benevides, M.R.F., Revisão de Cren¸ cas em Conjuntos de CláusulasSchool: COPPE/UFRJ, Rio de Janeiro-RJ, BRAZIL, 1993. [BibTeX]
BibTeX: @techreport{rodrigues-benevides93, author = {O. Rodrigues and M. R. F. Benevides}, title = {Revisão de Cren¸ cas em Conjuntos de Cláusulas}, school = {COPPE/UFRJ, Rio de Janeiro-RJ, BRAZIL}, year = {1993}, note = {Publica¸ cões Técnicas, ES-281/93} }
1992	Rodrigues, O. and Benevides, M.R.F., Prolog Modal de Ação, Anais do IX SBIA, pp. 339-357, 1992. [BibTeX]
BibTeX: @inproceedings{rodrigues-benevides92, author = {O. Rodrigues and M. R. F. Benevides}, title = {Prolog Modal de Ação}, booktitle = {Anais do IX SBIA}, year = {1992}, pages = {339-357} }