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PRICAI
1999
Springer
15 years 2 months ago
Rationality of Reward Sharing in Multi-agent Reinforcement Learning
Abstract. In multi-agent reinforcement learning systems, it is important to share a reward among all agents. We focus on the Rationality Theorem of Profit Sharing [5] and analyze ...
Kazuteru Miyazaki, Shigenobu Kobayashi
CEEMAS
2001
Springer
15 years 2 months ago
UML for Behavior-Oriented Multi-agent Simulations
Developing multi-agent simulations seems to be rather straight forward, as active entities in the original correspond to active agents in the model. Thus plausible behaviors can be...
Christoph Oechslein, Franziska Klügl, Rainer ...
ATAL
2010
Springer
14 years 11 months ago
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
W. Bradley Knox, Peter Stone
ATAL
2010
Springer
14 years 11 months ago
Evolving policy geometry for scalable multiagent learning
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
IDA
2011
Springer
14 years 4 months ago
Ubiquitous Knowledge Discovery
Ubiquitous Knowledge Discovery is a new research area at the intersection of machine learning and data mining with mobile and distributed systems. In this paper the main character...
João Gama, Michael May