Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Intelligent systems are often called upon to form plans that direct their own or other agents' activities. For these systems, the ability to describe plans to people in natur...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
We investigate the behaviour of load-adaptive rerouting policies in the Wardrop model where decisions must be made on the basis of stale information. In this model, an infinite n...
Some benefits of a dialogue between evolutionary robotics and developmental ethology are presented with discussion of how developmental models might inform approaches to evolution...