NP-completeness of the set unification and matching problems
Proc. of the 8th international conference on Automated deduction
A new deductive approach to planning
New Generation Computing
Learning to act using real-time dynamic programming
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
Planning under time constraints in stochastic domains
Artificial Intelligence - Special volume on planning and scheduling
A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
LAO: a heuristic search algorithm that finds solutions with loops
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Symbolic heuristic search for factored Markov decision processes
Eighteenth national conference on Artificial intelligence
Dynamic Programming
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Exploiting first-order regression in inductive policy selection
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
The first probabilistic track of the international planning competition
Journal of Artificial Intelligence Research
Symbolic dynamic programming for first-order MDPs
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
SPUDD: stochastic planning using decision diagrams
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
θ-Subsumption Based on Object Context
Inductive Logic Programming
First order decision diagrams for relational MDPs
Journal of Artificial Intelligence Research
Generalized first order decision diagrams for first order Markov decision processes
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Learning models of relational MDPs using graph kernels
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Generating optimal plans in highly-dynamic domains
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Automatic induction of bellman-error features for probabilistic planning
Journal of Artificial Intelligence Research
Decision-theoretic planning with generalized first-order decision diagrams
Artificial Intelligence
Probabilistic relational planning with first order decision diagrams
Journal of Artificial Intelligence Research
Exploration in relational domains for model-based reinforcement learning
The Journal of Machine Learning Research
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We present a heuristic search algorithm for solving first-order Markov Decision Processes (FOMDPs). Our approach combines first-order state abstraction that avoids evaluating states individually, and heuristic search that avoids evaluating all states. Firstly, in contrast to existing systems, which start with propositionalizing the FOMDP and then perform state abstraction on its propositionalized version we apply state abstraction directly on the FOMDP avoiding propositionalization. This kind of abstraction is referred to as first-order state abstraction. Secondly, guided by an admissible heuristic, the search is restricted to those states that are reachable from the initial state. We demonstrate the usefulness of the above techniques for solving FOMDPs with a system, referred to as FluCaP (formerly, FCPlanner), that entered the probabilistic track of the 2004 International Planning Competition (IPC'2004) and demonstrated an advantage over other planners on the problems represented in first-order terms.