We report on an investigation of the learning of coordination in cooperative multi-agent systems. Specifically, we study solutions that are applicable to independent agents i.e. ...
Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. ...
Abstract. How can artificial or natural agents autonomously gain understanding of its own internal (sensory) state? This is an important question not just for physically embodied ...
Abstract-- Policy Gradients with Parameter-based Exploration (PGPE) is a novel model-free reinforcement learning method that alleviates the problem of high-variance gradient estima...
Frank Sehnke, Alex Graves, Christian Osendorfer, J...
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 ...
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...