Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Symbolic model checking: 1020 states and beyond
Information and Computation - Special issue: Selections from 1990 IEEE symposium on logic in computer science
Acting optimally in partially observable stochastic domains
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Planning under time constraints in stochastic domains
Artificial Intelligence - Special volume on planning and scheduling
Proceedings of the NATO Advanced Study Institute on Deductive program design
Planning control rules for reactive agents
Artificial Intelligence
Representing action: indeterminacy and ramifications
Artificial Intelligence
Planning via Model Checking: A Decision Procedure for AR
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Automatic SAT-compilation of planning problems
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
STRIPS: a new approach to the application of theorem proving to problem solving
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Universal plans for reactive robots in unpredictable environments
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Real-time search in non-deterministic domains
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
OBDD-based planning with real-valued variables in non-deterministic environments
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Symbolic Heuristic Search Using Decision Diagrams
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
Extending Multi-agent Cooperation by Overhearing
CooplS '01 Proceedings of the 9th International Conference on Cooperative Information Systems
NUSMV: A New Symbolic Model Verifier
CAV '99 Proceedings of the 11th International Conference on Computer Aided Verification
Solving the Entailment Problem in the Fluent Calculus Using Binary Decision Diagrams
CL '00 Proceedings of the First International Conference on Computational Logic
Symbolic heuristic search for factored Markov decision processes
Eighteenth national conference on Artificial intelligence
Weak, strong, and strong cyclic planning via symbolic model checking
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
A model for abstract process specification, verification and composition
Proceedings of the 2nd international conference on Service oriented computing
Conformant planning via symbolic model checking and heuristic search
Artificial Intelligence
Understanding planning with incomplete information and sensing
Artificial Intelligence
Automatic workflow verification and generation
Theoretical Computer Science
Limits and Possibilities of BDDs in State Space Search
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
Task decomposition on abstract states, for planning under nondeterminism
Artificial Intelligence
Weighted A∗ search -- unifying view and application
Artificial Intelligence
Regression with respect to sensing actions and partial states
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
OBDD-based universal planning for synchronized agents in non-deterministic domains
Journal of Artificial Intelligence Research
Conformant planning via symbolic model checking
Journal of Artificial Intelligence Research
Taming numbers and durations in the model checking integrated planning system
Journal of Artificial Intelligence Research
Engineering benchmarks for planning: the domains used in the deterministic part of IPC-4
Journal of Artificial Intelligence Research
Constructing conditional plans by a theorem-prover
Journal of Artificial Intelligence Research
Observation reduction for strong plans
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Planning in nondeterministic domains under partial observability via symbolic model checking
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Planning as model checking for extended goals in non-deterministic domains
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Understanding planning with incomplete information and sensing
Artificial Intelligence
Action Planning for Directed Model Checking of Petri Nets
Electronic Notes in Theoretical Computer Science (ENTCS)
Algorithms for memory hierarchies: advanced lectures
Algorithms for memory hierarchies: advanced lectures
SPIN'03 Proceedings of the 10th international conference on Model checking software
Active learning of plans for safety and reachability goals with partial observability
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new representation and associated algorithms for generalized planning
Artificial Intelligence
SPUDD: stochastic planning using decision diagrams
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A universal planning system for hybrid domains
Applied Intelligence
SAP speaks PDDL: exploiting a software-engineering model for planning in business process management
Journal of Artificial Intelligence Research
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Most real world environments are non-deterministic. Automatic plan formation in non-deterministic domains is, however, still an open problem. In this paper we present a practical algorithm for the automatic generation of solutions to planning problems in nondeterministic domains. Our approach has the followmg main features. First, the planner generates Universal Plans. Second, it generates plans which are guaranteed to achieve the goal in spite of non-determinism, if such plans exist. Otherwise, the planner generates plans which encode iterative trial-and-error strategies (e.g. try to pick up a block until succeed), which are guaranteed to achieve the goal under the assumption that if there is a non-deterministic possibility for the iteration to terminate, this will not be ignored forever. Third, the implementation of the planner is based on symbolic model checking techniques which have been designed to explore efficiently large state spaces. The implementation exploits the compactness of OBDDS (Ordered Binary Decision Diagrams) to express in a practical way universal plans of extremely large size.