Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
SOAR: an architecture for general intelligence
Artificial Intelligence
Practical planning: extending the classical AI planning paradigm
Practical planning: extending the classical AI planning paradigm
Frames in the space of situations (research note)
Artificial Intelligence
Proving properties of states in the situation calculus
Artificial Intelligence
Artificial Intelligence
Fast planning through planning graph analysis
Artificial Intelligence
Control knowledge in planning: benefits and tradeoffs
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
Using temporal logics to express search control knowledge for planning
Artificial Intelligence
Open World Planning in the Situation Calculus
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Extending Planning Graphs to an ADL Subset
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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We present a representation scheme for the declarative formalization of strategies for action selection based on the situation calculus and circumscription. The formalism is applied to represent a number of heuristics for moving blocks in order to solve planning problems in the blocks world. The formal model of a heuristic forward chaining planner, which can take advantage of declarative formalizations of strategies for action selection, is proposed. Experiments showing how the use of declarative representations of strategies for action selection allows a heuristic forward chaining planner to improve the performance of state of the art planning systems are described.