POMDPs and their decentralized multiagent counterparts, DEC-POMDPs, offer a rich framework for sequential decision making under uncertainty. Their computational complexity, howeve...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
The options framework provides a method for reinforcement learning agents to build new high-level skills. However, since options are usually learned in the same state space as the...
The application of AI planning techniques to manufacturing systems is being widely deployed for all the tasks involved in the process, from product design to production planning an...
Multi-agent systems (MAS) provide a promising technology for addressing problems such as search and rescue missions, mine sweeping, and surveillance. These problems are a form of ...
Evidence theory has been widely applied to uncertainty reasoning. In this paper a finite state machine with evidential reasoning is proposed to control autonomous robots. The Khep...
Qingxiang Wu, David A. Bell, Rashid Hafeez Khokhar...