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I am particularly interested in planning for problems where time matters and/or where there are costs and rewards on actions.
these are inter-related. Anyone who has bought a train ticket to London
will know that the time of day
matters: it affects the cost of the ticket, and the transport options
available. We could find a plan by ignoring time, just making sure the
legs of the journey are connected, but it wouldn't be a great plan: we
might have to wait a long time for a connection, or pay a high fare.
Thus, for automated planning to really be useful here, it has to take
time (and costs) into account.
This phenomenon arises in all sorts of interesting problems. One project I am involved in is looking at Planning Surveillance Activities.
For instance, if we are trying to locate people who have been stranded
after flooding, and we have some information about where they were last
seen, and in which direction they were heading, then this informs our
plan of where to go and when, to maximise the likelihood of finding
them. Of course, this is hard, but all the most interesting research
problems are hard.
So what is a planner?
A planner is a piece of software. It takes a description of
the current state of the world; the actions that could be taken; and the
goals that need to be met. Using a combination of techniques, it then searches for a plan, by considering various sequences of actions. Most of my work is on developing anytime planners that try to find some plan quickly; then carry on searching to find a better one.
I have written several planners over the years. They are all freely available.
OPTIC is a temporal planner for use in problems where plan cost
is determined by preferences or time-dependent goal-collection costs.
Such problems arise in a range of interesting situations, from
scheduling the delivery of perishable goods, to coordinating
order-fulfillment activities in warehouses.
Find out more about OPTIC »
The award-winning planner POPF was inspired by the idea of
searching forwards for a plan from the initial state, whilst minimising
the number of ordering constraints added between the actions in
the plan. This leads to plans that have greater scope for performing
actions in parallel, and consequently, complete in less time.
Find out more about POPF »
COLIN was the first PDDL planner to support (linear) continuous numeric change. A common use for this capability is modelling numeric resource levels
such as battery charged that are continuously changed by an action, and
need to be managed carefully in order to produce a plan.
Find out more about COLIN »
See my profile on Google Scholar or the King's PURE system, though the former is more complete.
Programme Committee Memberships
- Artificial Intelligence (AIJ)
- Journal of Artificial Intelligence Research (JAIR)
- Journal of Scheduling (JOSH)
- Annals of Mathematics and Artificial Intelligence (AMAI)
- ACM Transactions on Intelligent Systems and Technology (ACM TIST)
- International Journal of AI Tools (IJAIT)
- AI Communications (AIComms)
- International Conference on Automated Planning and Scheduling (ICAPS) 2007, 2008
- Doctoral Consortium Talk — ICAPS 2012, Brazil, June 2012
- Tutorial on Temporal and Continuous Planning — Austrian Robotics Workshop, May 2011
- Temporal Planning: POPping Forwards — Robert Gordon University, Aberdeen, March 2011
- Combining PEPA and Stochastic Planning to meet
Service-Level Agreements — Second SICSA Workshop on Probabilistic
Modelling, Model-Checking and Planning, University of Glasgow, December
- Planning Analyses for PEPA Models — University of Edinburgh, January 2010
- Challenges in Temporal–Numeric Planning — University of Birmingham, January 2010
- Planning for Processes and Pathways — SICSA Modelling and Abstraction Theme Meeting, January 2010
- Applying AI Planning to Substation Voltage Control —
Presentation to John Beddington CMG FRS (Chief Scientific Advisor to the
UK Government), Royal Society of Edinburgh, February 2009.