After two decades of research on automated discovery, many principles are shaping up as a foundation of discovery science. In this paper we view discovery science as automation of ...
We present new results from a real-user evaluation of a data-driven approach to learning user-adaptive referring expression generation (REG) policies for spoken dialogue systems. ...
Our goal is to provide learning mechanisms to game agents so they are capable of adapting to new behaviors based on the actions of other agents. We introduce a new on-line reinfor...
Comparing humans and machines is one important source of information about both machine and human strengths and limitations. Most of these comparisons and competitions are performe...
Javier Insa-Cabrera, David L. Dowe, Sergio Espa&nt...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...