This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Abstract This paper presents a framework for the generation of coherent elementary conversational sequences at the speech act level. We will embrace the notion of a cooperative dia...
We present a study of people’s use of positional information as part of a collaborative location-based game. The game exploits self-reported positioning in which mobile players m...
Steve Benford, Will Seager, Martin Flintham, Rob A...
Abstract. Case-based planning (CBP) is based on reusing past successful plans for solving new problems. CBP is particularly useful in environments where the large amount of time re...
We explore an application to the game of Go of a reinforcement learning approach based on a linear evaluation function and large numbers of binary features. This strategy has prov...