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» Opposition-Based Reinforcement Learning
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IJCAI
2001
13 years 11 months ago
Rational and Convergent Learning in Stochastic Games
This paper investigates the problem of policy learning in multiagent environments using the stochastic game framework, which we briefly overview. We introduce two properties as de...
Michael H. Bowling, Manuela M. Veloso
ATAL
2004
Springer
14 years 3 months ago
A Pheromone-Based Utility Model for Collaborative Foraging
Multi-agent research often borrows from biology, where remarkable examples of collective intelligence may be found. One interesting example is ant colonies’ use of pheromones as...
Liviu Panait, Sean Luke
ISADS
1999
IEEE
14 years 2 months ago
Emergence of Communication for Negotiation by a Recurrent Neural Network
We believe that communication in multi-agent system has two major meanings. One of them is to transmit one agent's observed information to the other. The other meaning is to ...
Katsunari Shibata, Koji Ito
ATAL
2008
Springer
14 years 23 hour ago
Sequential decision making with untrustworthy service providers
In this paper, we deal with the sequential decision making problem of agents operating in computational economies, where there is uncertainty regarding the trustworthiness of serv...
W. T. Luke Teacy, Georgios Chalkiadakis, Alex Roge...
CEC
2008
IEEE
14 years 15 hour ago
Learning benefits evolution if sex gives pleasure
Abstract-- In this paper we investigate the effects of individual learning on an evolving population of situated agents. We work with a novel type of system where agents can decide...
Robert Griffioen, Selmar K. Smit, A. E. Eiben