The aim of this work is the design of a framework for the revision of knowledge in abductive reasoning agents, based on interaction. We address issues such as: how to exploit knowl...
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
This paper is concerned with personalisation of user agents by symbolic, on-line machine learning techniques. The application of these ideas to an infotainment agent is discussed ...
Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee S...
Some natural epistemic properties which may arise in applications can only be expressed in standard epistemic logic by formulae which are exponentially long in the number of agent...
The reason for using distributed constraint satisfaction algorithms is often to allow agents to find a solution while revealing as little as possible about their variables and co...