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NPL
2000
105views more  NPL 2000»
13 years 7 months ago
Online Interactive Neuro-evolution
In standard neuro-evolution, a population of networks is evolved in a task, and the network that best solves the task is found. This network is then fixed and used to solve future...
Adrian K. Agogino, Kenneth O. Stanley, Risto Miikk...
AI
2006
Springer
13 years 11 months ago
Satisfaction Equilibrium: Achieving Cooperation in Incomplete Information Games
So far, most equilibrium concepts in game theory require that the rewards and actions of the other agents are known and/or observed by all agents. However, in real life problems, a...
Stéphane Ross, Brahim Chaib-draa
ECAL
2007
Springer
14 years 1 months ago
Neuroevolution of Agents Capable of Reactive and Deliberative Behaviours in Novel and Dynamic Environments
Both reactive and deliberative qualities are essential for a good action selection mechanism. We present a model that embodies a hybrid of two very diļ¬€erent neural network archit...
Edward Robinson, Timothy Ellis, Alastair Channon
AI
1999
Springer
13 years 7 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
CEEMAS
2003
Springer
14 years 19 days ago
On a Dynamical Analysis of Reinforcement Learning in Games: Emergence of Occam's Razor
Modeling learning agents in the context of Multi-agent Systems requires an adequate understanding of their dynamic behaviour. Usually, these agents are modeled similar to the diļ¬...
Karl Tuyls, Katja Verbeeck, Sam Maes