Multiagent environments are often highly dynamic and only partially observable which makes deliberative action planning computationally hard. In many such environments, however, a...
The importance of the problems of contingent planning with actions that have non-deterministic effects and of planning with goal preferences has been widely recognized, and severa...
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
— A new hybrid motion planning technique based on Harmonic Functions (HF) and Probabilistic Roadmaps (PRM) is presented. The proposed approach consists of incrementally building ...
Navigationalpath planning is a classicalproblem in autonomous mobile robotics. Most AI approachesto path planning use goal-directedheuristicsearch of problem spaces defined by spa...
Ashok K. Goel, Michael W. Donnellan, Nancy Vazquez...