This work presents a new algorithm, called Heuristically Accelerated Q–Learning (HAQL), that allows the use of heuristics to speed up the well-known Reinforcement Learning algori...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
Planners from the family of Graphplan (Graphplan, IPP, STAN...) are presently considered as the most efficient ones on numerous planning domains. Their partially ordered plans can...
Dealing with numerical information is practically important in many real-world planning domains where the executability of an action can depend on certain numerical conditions, an...
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...
We propose a new incomplete algorithm for the Maximum Satisfiability (MaxSAT) problem on unweighted Boolean formulas, focused specifically on instances for which proving unsatis...