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» Models of active learning in group-structured state spaces
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LAMAS
2005
Springer
15 years 3 months ago
Multi-agent Relational Reinforcement Learning
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
RSS
2007
176views Robotics» more  RSS 2007»
14 years 11 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
IJON
2007
120views more  IJON 2007»
14 years 9 months ago
Comparison of dynamical states of random networks with human EEG
Existing models of EEG have mainly focused on relations to network dynamics characterized by firing rates [L. de Arcangelis, H.J. Herrmann, C. Perrone-Capano, Activity-dependent ...
Ralph Meier, Arvind Kumar, Andreas Schulze-Bonhage...
ICML
2009
IEEE
15 years 4 months ago
Active learning for directed exploration of complex systems
Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fid...
Michael C. Burl, Esther Wang
87
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TSMC
2010
14 years 4 months ago
Active Learning of Plans for Safety and Reachability Goals With Partial Observability
Traditional planning assumes reachability goals and/or full observability. In this paper, we propose a novel solution for safety and reachability planning with partial observabilit...
Wonhong Nam, Rajeev Alur