A model for reasoning about persistence and causation
Computational Intelligence
An algorithm for probabilistic planning
Artificial Intelligence - Special volume on planning and scheduling
Abstraction and approximate decision-theoretic planning
Artificial Intelligence
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Learning measures of progress for planning domains
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Efficient solution algorithms for factored MDPs
Journal of Artificial Intelligence Research
PDDL2.1: an extension to PDDL for expressing temporal planning domains
Journal of Artificial Intelligence Research
The computational complexity of probabilistic planning
Journal of Artificial Intelligence Research
Exploiting structure in policy construction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Probabilistic propositional planning: representations and complexity
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
SPUDD: stochastic planning using decision diagrams
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
θ-Subsumption Based on Object Context
Inductive Logic Programming
Practical solution techniques for first-order MDPs
Artificial Intelligence
Decision making in large-scale domains: a case study
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Generating plans in concurrent, probabilistic, over-subscribed domains
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Engineering a conformant probabilistic planner
Journal of Artificial Intelligence Research
Decision-theoretic planning with non-Markovian rewards
Journal of Artificial Intelligence Research
Engineering benchmarks for planning: the domains used in the deterministic part of IPC-4
Journal of Artificial Intelligence Research
FLUCAP: a heuristic search planner for first-order MDPs
Journal of Artificial Intelligence Research
Exploring compact reinforcement-learning representations with linear regression
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Adversarial reasoning under uncertainty using a deterministic planner
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Planning interventions in biological networks
ACM Transactions on Intelligent Systems and Technology (TIST)
Human-aware task planning: An application to mobile robots
ACM Transactions on Intelligent Systems and Technology (TIST)
Automatic induction of bellman-error features for probabilistic planning
Journal of Artificial Intelligence Research
Probabilistic relational planning with first order decision diagrams
Journal of Artificial Intelligence Research
Stochastic enforced hill-climbing
Journal of Artificial Intelligence Research
Imitation learning in relational domains: a functional-gradient boosting approach
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Exploiting probabilistic knowledge under uncertain sensing for efficient robot behaviour
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
SAP speaks PDDL: exploiting a software-engineering model for planning in business process management
Journal of Artificial Intelligence Research
Finding objects through stochastic shortest path problems
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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The 2004 International Planning Competition, IPC-4, included a probabilistic planning track for the first time. We describe the new domain specification language we created for the track, our evaluation methodology, the competition domains we developed, and the results of the participating teams.