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...
This article investigates fundamental issues in scaling autonomous personal robots towards open-ended sets of everyday manipulation tasks which involve high complexity and vague j...
POMDPs are a popular framework for representing decision making problems that contain uncertainty. The high computational complexity of finding exact solutions to POMDPs has spaw...
Abstract. We present a declarative language, PP, for the specification of preferences between possible solutions (or trajectories) of a planning problem. This novel language allow...
In this paper, we introduce a tile-graph-based approach to power planning. For a given flooplan solution, the power inputs are modeled into a tile graph, the minimum capacity of e...