Toward a mathematical theory of plan synthesis
Toward a mathematical theory of plan synthesis
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
Computational complexity of planning and approximate planning in the presence of incompleteness
Artificial Intelligence
Formalizing sensing actions—a transition function based approach
Artificial Intelligence
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowledge, action, and the frame problem
Artificial Intelligence
Action representation and partially observable planning using epistemic logic
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Conditional planning in the discrete belief space
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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This paper develops a state-based regression method for planning domains with sensing operators and a representation of the knowledge of the planning agent. The language includes primitive actions, sensing actions, and conditional plans. We prove the soundness and completeness of the regression formulation with respect to the definition of progression and the semantics of a propositional modal logic of knowledge. It is our expectation that this work will serve as the foundation for the extension of recently successful work on state-based regression planning to include sensing and knowledge as well.