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» A New Way to Introduce Knowledge into Reinforcement Learning
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DIS
1999
Springer
15 years 4 months ago
The Melting Pot of Automated Discovery: Principles for a New Science
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 ...
Jan M. Zytkow
SIGDIAL
2010
14 years 9 months ago
Adaptive Referring Expression Generation in Spoken Dialogue Systems: Evaluation with Real Users
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. ...
Srinivasan Janarthanam, Oliver Lemon
AIIDE
2009
15 years 27 days ago
Learning Character Behaviors Using Agent Modeling in Games
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...
Richard Zhao, Duane Szafron
AGI
2011
14 years 3 months ago
Comparing Humans and AI Agents
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...
ATAL
2010
Springer
15 years 27 days ago
Learning multi-agent state space representations
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 ...
Yann-Michaël De Hauwere, Peter Vrancx, Ann No...