Technical Note: \cal Q-Learning
Machine Learning
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Multiagent learning using a variable learning rate
Artificial Intelligence
Nash q-learning for general-sum stochastic games
The Journal of Machine Learning Research
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
A logic of emotions for intelligent agents
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Efficient reinforcement learning in factored MDPs
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Coordinated learning in multiagent MDPs with infinite state-space
Autonomous Agents and Multi-Agent Systems
Social conformity and its convergence for reinforcement learning
MATES'10 Proceedings of the 8th German conference on Multiagent system technologies
Influence of FFM/NEO PI-R personality traits on the rational process of autonomous agents
Web Intelligence and Agent Systems
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Individuals inside a society can make organizational changes by modifying their behavior. These changes can be guided by the outcome of the actions of every individual in the society. Should the outcome be worse than expected, they would innovate to find a better solution to adapt the society to the new situation automatically. Following these ideas, a novel social agent model, based on emotions and social welfare, is proposed in this paper. Also, a learning algorithm based on this model, as well as a case of study to test its validity, are given.