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AIIDE
2008
13 years 10 months ago
Combining Model-Based Meta-Reasoning and Reinforcement Learning for Adapting Game-Playing Agents
Human experience with interactive games will be enhanced if the software agents that play the game learn from their failures. Techniques such as reinforcement learning provide one...
Patrick Ulam, Joshua Jones, Ashok K. Goel
IADIS
2004
13 years 9 months ago
Computer-mediated communication: what can we learn from a diverse range of users?
The demographics of computer-mediated communication (CMC) users have changed considerably over the last twenty years. Whereas in the 1980's it was largely academics, and comp...
Sanjeet Bhachu, D. Ramanee Peiris, Annalu Waller
HT
2009
ACM
14 years 2 months ago
Improving recommender systems with adaptive conversational strategies
Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...
Tariq Mahmood, Francesco Ricci
NIPS
2003
13 years 9 months ago
All learning is Local: Multi-agent Learning in Global Reward Games
In large multiagent games, partial observability, coordination, and credit assignment persistently plague attempts to design good learning algorithms. We provide a simple and efï¬...
Yu-Han Chang, Tracey Ho, Leslie Pack Kaelbling
ATAL
2007
Springer
14 years 1 months ago
Automatic feature extraction for autonomous general game playing agents
The General Game Playing (GGP) problem is concerned with developing systems capable of playing many different games, even games the system has never encountered before. Successful...
David M. Kaiser