Recent research has addressed the problem of planning in non-deterministic domains. Classical planning has also been extended to the case of goals that can express temporal proper...
Multi-agent planning is a fundamental problem in multiagent systems that has acquired a variety of meanings in the relative literature. In this paper we focus on a setting where m...
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
Compared to optimal planners, satisficing planners can solve much harder problems but may produce overly costly and long plans. Plan quality for satisficing planners has become in...
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently guide the problem-space exploration. Machine learning (ML) provides several tec...