Constraint satisfaction in logic programming
Constraint satisfaction in logic programming
Conditional nonlinear planning
Proceedings of the first international conference on Artificial intelligence planning systems
An algorithm for probabilistic least-commitment planning
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
An Interactive Constraint-Based System for Selective Attention in Visual Search
ISMIS '97 Proceedings of the 10th International Symposium on Foundations of Intelligent Systems
Information Gathering Plans With Sensing Actions
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Planning and knowledge representation for softbots
Planning and knowledge representation for softbots
Constraint propagation and value acquisition: why we should do it interactively
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Planning executing sensing and replanning for information gathering
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A 25-year perspective on logic programming
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We propose a planning architecture where the planner and the executor interact with each other in order to face dynamic changes of the application domain. According to the deferred planning strategy proposed in [14], a plan schema is produced off-line by a generative constraint based planner and refined at execution time by retrieving up-to-date information when that available is no longer valid. In this setting, both planning and execution can be seen as search processes in the space of partial plans. We exploit the Interactive Constraint Satisfaction framework [12] which represents an extension of the Constraint Satisfaction paradigm for dealing with incomplete knowledge. Given the uncertainty of the plan execution in dynamic environments, a backup and recovery mechanism is necessary in order to allow backtracking at execution time.