Markov Decision Processes (MDPs), currently a popular method for modeling and solving decision theoretic planning problems, are limited by the Markovian assumption: rewards and dy...
This paper explores the use of an oft-ignored information source in heuristic search: a search-distance-to-go estimate. Operators frequently have different costs and cost-to-go is...
— Synthesis of robot behaviors towards nontrivial goals often requires reasoning about both discrete and continuous aspects of the underlying domain. Existing approaches in build...
In this paper we present an educational tool which has been designed to manage (learning) knowledge acquired from the interactions with the students, and to automatically aids educ...
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...