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ICCBR
2010
Springer
15 years 4 months ago
Imitating Inscrutable Enemies: Learning from Stochastic Policy Observation, Retrieval and Reuse
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
JAIR
2002
122views more  JAIR 2002»
15 years 13 days ago
Competitive Safety Analysis: Robust Decision-Making in Multi-Agent Systems
Much work in AI deals with the selection of proper actions in a given (known or unknown) environment. However, the way to select a proper action when facing other agents is quite ...
Moshe Tennenholtz
TCIAIG
2010
14 years 7 months ago
Learning to Drive in the Open Racing Car Simulator Using Online Neuroevolution
In this paper, we applied online neuroevolution to evolve nonplayer characters for The Open Racing Car Simulator (TORCS). While previous approaches allowed online learning with per...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
SODA
2012
ACM
278views Algorithms» more  SODA 2012»
13 years 3 months ago
Beyond myopic best response (in Cournot competition)
A Nash Equilibrium is a joint strategy profile at which each agent myopically plays a best response to the other agents’ strategies, ignoring the possibility that deviating fro...
Amos Fiat, Elias Koutsoupias, Katrina Ligett, Yish...
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
16 years 1 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...