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AAAI
2000
15 years 7 months ago
Defining and Using Ideal Teammate and Opponent Agent Models
A common challenge for agents in multiagent systems is trying to predict what other agents are going to do in the future. Such knowledge can help an agent determine which of its c...
Peter Stone, Patrick Riley, Manuela M. Veloso
AIIDE
2009
15 years 7 months ago
Improving Offensive Performance Through Opponent Modeling
Although in theory opponent modeling can be useful in any adversarial domain, in practice it is both difficult to do accurately and to use effectively to improve game play. In thi...
Kennard Laviers, Gita Sukthankar, David W. Aha, Ma...
JAIR
2011
187views more  JAIR 2011»
15 years 1 months ago
A Monte-Carlo AIXI Approximation
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
IUI
2009
ACM
16 years 3 months ago
An interface for targeted collection of common sense knowledge using a mixture model
We present a game-based interface for acquiring common sense knowledge. In addition to being interactive and entertaining, our interface guides the knowledge acquisition process t...
Robert Speer, Jayant Krishnamurthy, Catherine Hava...
ATAL
2003
Springer
15 years 11 months ago
A selection-mutation model for q-learning in multi-agent systems
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
Karl Tuyls, Katja Verbeeck, Tom Lenaerts