Contact

Room 3.51, Informatics Forum
10 Crichton Street
Edinburgh, EH8 9AB
Email: M.Crosby [at] ed.ac.uk
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About

I am a Postdoctoral Research Associate at the University of Edinburgh currently working on the EU STAMINA project. My main research interest is automated planning with a bias towards multiagent planning. In general I like pretty much anything involving well-defined problems that permit some kind of lateral thinking step in their solutions or solution methods.

Publications

ADP: an Agent Decomposition Planner CoDMAP 2015 Matthew Crosby, ICAPS Proceedings of the Competition of Distributed and Multi-Agent Planners (CodMAP) 2015 [pdf]
A Single-Agent Approach to Multiagent Planning Matthew Crosby, Anders Jonsson, and Michael Rovatsos, 21st European Conference on Artificial Intelligence (ECAI) 2014 [pdf]
Improving Planner Performance in Grid Worlds with Macro Actions Matthew Crosby and Ronald Petrick, The 9th International Workshop on Cognitive Robotics (CogRob) at the 21st European Conference on Artificial Intelligence (ECAI) 2014 (Short Paper) [pdf]
Temporal Multiagent Planning with Concurrent Action Constraints M.Crosby, R.Petrick, Distributed and Multiagent Planning workshop (DMAP) at the International Conference on Automated Planning and Scheduling (ICAPS) 2014 [pdf]
Multiagent Classical Planning M.Crosby, PhD Thesis 2014 [pdf]
A Temporal Approach to Multiagent Planning with Concurrent Actions M.Crosby, Workshop of the UK Planning and Scheduling Special Interest Group (PlanSig) 2013 (Tech. Report) [pdf]
Automated Agent Decomposition for Classical Planning M.Crosby, M.Rovatsos and R.Petrick, International Conference on Automated Planning and Scheduling (ICAPS) 2013 [pdf]
Heuristic Multiagent Planning with Self-Interested Agents M.Crosby and M.Rovatsos, International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2011 (Extended Abstract) [pdf]
Evolving a Roving Eye for Go M.Crosby, Master's Thesis 2008 [pdf]

Code

ADP Planner (including the snapshot of Fast-Downward it was built for) can be found here. After compiling, run with the option --heuristic 'hff=adp(cost_type=1)' --search 'lazy_greedy(hff, preferred=hff)'

Python ma-PDDL Parser ppp.py: for translating multiagent pddl with concurrent action constraints to temporal planning problems (see DMAP 2014 paper [pdf]). The code is in need of some work so use at your own risk.