Domain-independent planning: representation and plan generation
Artificial Intelligence
Practical planning: extending the classical AI planning paradigm
Practical planning: extending the classical AI planning paradigm
Handbook of theoretical computer science (vol. B)
Conditional nonlinear planning
Proceedings of the first international conference on Artificial intelligence planning systems
Planning control rules for reactive agents
Artificial Intelligence
Extending Graphplan to handle uncertainty and sensing actions
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Automata-Theoretic Approach to Planning for Temporally Extended Goals
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
Planning with a language for extended goals
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
Generating safe assumption-based plans for partially observable, nondeterministic domains
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
Planning for contingencies: a decision-based approach
Journal of Artificial Intelligence Research
Constructing conditional plans by a theorem-prover
Journal of Artificial Intelligence Research
Improvements to the evaluation of quantified boolean formulae
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
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
Time-saving tips for problem solving with incomplete information
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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Several application domains require planning techniques that model uncertainty in the results of both actions and observations. Actions may have different effects that cannot be predicted at planning time. Observations may result into uncertainty about the current state of the world. In this paper, we first discuss the problem of planning with uncertainty in action execution and observations. We then discuss how this problem can be relevant to different application domains that represent rather different characteristics, like planning for controlling a robot that has to perform a surveillance task, as well as planning for the automated composition of web services for e-commerce.