In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
d Abstract) We extend the model of [VRV94] to express strong time-outs (and pre-emption): if an event A does not happen through time t, cause event B to happen at time t. Such con...
— Mobile robot localization and navigation requires a map - the robot’s internal representation of the environment. A common problem is that path planning becomes very ineffic...
Automatically constructing novel representations of tasks from analysis of state spaces is a longstanding fundamental challenge in AI. I review recent progress on this problem for...
We define TTD-MDPs, a novel class of Markov decision processes where the traditional goal of an agent is changed from finding an optimal trajectory through a state space to realiz...
David L. Roberts, Mark J. Nelson, Charles Lee Isbe...