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» Models of active learning in group-structured state spaces
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LAMAS
2005
Springer
15 years 10 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»
15 years 6 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»
15 years 4 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 11 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
TSMC
2010
14 years 11 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