Multi-robot learning faces all of the challenges of robot learning with all of the challenges of multiagent learning. There has been a great deal of recent research on multiagent ...
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Most of the proposed approaches in automatic service selection assume the existence of a common ontology among communicating agents. However, this assumption becomes difficult to...
This paper introduces TUTW – Temporal Uncertainty Time Warp – a control engine designed for an exploitation of temporal uncertainty (TU) in general optimistic simulations, and...
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...