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BC
1998
109views more  BC 1998»
15 years 15 days ago
Learning and stabilization of altruistic behaviors in multi-agent systems by reciprocity
Optimization of performance in collective systems often requires altruism. The emergence and stabilization of altruistic behaviors are dicult to achieve because the agents incur ...
Javier Zamora, José del R. Millán, A...
ATAL
2009
Springer
14 years 10 months ago
Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach
Today's society is largely connected and many real life applications lend themselves to be modeled as multi-agent systems. Although such systems as well as their models are d...
Michael Kaisers, Karl Tuyls
146
Voted
JMLR
2012
13 years 3 months ago
Contextual Bandit Learning with Predictable Rewards
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Alekh Agarwal, Miroslav Dudík, Satyen Kale,...
135
Voted
ICCBR
2009
Springer
15 years 7 months ago
Improving Reinforcement Learning by Using Case Based Heuristics
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...
Reinaldo A. C. Bianchi, Raquel Ros, Ramon Ló...
104
Voted
CORR
2002
Springer
100views Education» more  CORR 2002»
15 years 17 days ago
A neural model for multi-expert architectures
We present a generalization of conventional artificial neural networks that allows for a functional equivalence to multi-expert systems. The new model provides an architectural fr...
Marc Toussaint