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ATAL
2007
Springer
14 years 1 months ago
Reducing the complexity of multiagent reinforcement learning
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Andriy Burkov, Brahim Chaib-draa
CORR
2010
Springer
92views Education» more  CORR 2010»
13 years 7 months ago
Hardness Results for Agnostically Learning Low-Degree Polynomial Threshold Functions
Hardness results for maximum agreement problems have close connections to hardness results for proper learning in computational learning theory. In this paper we prove two hardnes...
Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Serve...
AAAI
2012
11 years 10 months ago
Learning Games from Videos Guided by Descriptive Complexity
In recent years, several systems have been proposed that learn the rules of a simple card or board game solely from visual demonstration. These systems were constructed for speciď...
Lukasz Kaiser
FOSSACS
2004
Springer
14 years 1 months ago
A Game Semantics of Local Names and Good Variables
We describe a game semantics for local names in a functional setting. It is based on a category of dialogue games acted upon by the automorphism group of the natural numbers; this ...
James Laird
27
Voted
IAT
2009
IEEE
13 years 11 months ago
Combining Boolean Games with the Power of Ontologies for Automated Multi-attribute Negotiation in the Semantic Web
Recently, multi-attribute negotiation has been extensively studied from a game-theoretic viewpoint. Since normal and extensive form games have the drawback of requiring an explicit...
Thomas Lukasiewicz, Azzurra Ragone