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AAAI
1998
13 years 7 months ago
The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems
Reinforcement learning can provide a robust and natural means for agents to learn how to coordinate their action choices in multiagent systems. We examine some of the factors that...
Caroline Claus, Craig Boutilier
WWW
2008
ACM
14 years 6 months ago
Secure or insure?: a game-theoretic analysis of information security games
Despite general awareness of the importance of keeping one's system secure, and widespread availability of consumer security technologies, actual investment in security remai...
Jens Grossklags, Nicolas Christin, John Chuang
UAI
2000
13 years 7 months ago
Learning to Cooperate via Policy Search
Cooperative games are those in which both agents share the same payoff structure. Valuebased reinforcement-learning algorithms, such as variants of Q-learning, have been applied t...
Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Les...
SAGA
2007
Springer
14 years 10 days ago
Probabilistic Techniques in Algorithmic Game Theory
We consider applications of probabilistic techniques in the framework of algorithmic game theory. We focus on three distinct case studies: (i) The exploitation of the probabilistic...
Spyros C. Kontogiannis, Paul G. Spirakis
AMAI
2004
Springer
13 years 11 months ago
A Framework for Sequential Planning in Multi-Agent Settings
This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
Piotr J. Gmytrasiewicz, Prashant Doshi