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ATAL
2010
Springer
15 years 8 months ago
Using graph analysis to study networks of adaptive agent
Experimental analysis of networks of cooperative learning agents (to verify certain properties such as the system's stability) has been commonly used due to the complexity of...
Sherief Abdallah
ATAL
2010
Springer
15 years 8 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
ATAL
2010
Springer
15 years 8 months ago
Hybrid transitive trust mechanisms
Establishing trust amongst agents is of central importance to the development of well-functioning multi-agent systems. For example, the anonymity of transactions on the Internet c...
Jie Tang, Sven Seuken, David C. Parkes
ATAL
2010
Springer
15 years 8 months ago
Linear options
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Jonathan Sorg, Satinder P. Singh
ATAL
2010
Springer
15 years 8 months ago
Learning multi-agent state space representations
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Yann-Michaël De Hauwere, Peter Vrancx, Ann No...
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