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ML
2006
ACM
113views Machine Learning» more  ML 2006»
14 years 11 months ago
Learning to bid in bridge
Bridge bidding is considered to be one of the most difficult problems for game-playing programs. It involves four agents rather than two, including a cooperative agent. In additio...
Asaf Amit, Shaul Markovitch
IJCIA
2002
137views more  IJCIA 2002»
14 years 11 months ago
Co-Evolution in Social Interactions
An interesting problem which has been widely investigated is under what circumstances will a society of rational agents realize some particular stable situations, and whether they ...
Hiroshi Sato, Akira Namatame
JAIR
2011
187views more  JAIR 2011»
14 years 6 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 ...
GECCO
2009
Springer
130views Optimization» more  GECCO 2009»
15 years 6 months ago
The impact of jointly evolving robot morphology and control on adaptation rate
Embodied cognition emphasizes that intelligent behavior results from the coupled dynamics between an agent’s body, brain and environment. In response to this, several projects h...
Josh C. Bongard
AAAI
2006
15 years 1 months ago
The Robot Intelligence Kernel
The Robot Intelligence Kernel (RIK) is a portable, reconfigurable suite of perceptual, behavioral, and cognitive capabilities that can be used across many different platforms, env...
David J. Bruemmer, Douglas A. Few, Miles C. Walton...