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IROS
2007
IEEE
123views Robotics» more  IROS 2007»
14 years 2 months ago
Reinforcement learning in multi-dimensional state-action space using random rectangular coarse coding and Gibbs sampling
: This paper presents a coarse coding technique and an action selection scheme for reinforcement learning (RL) in multi-dimensional and continuous state-action spaces following con...
Kimura Kimura
ICANNGA
2007
Springer
105views Algorithms» more  ICANNGA 2007»
14 years 2 months ago
Reinforcement Learning in Fine Time Discretization
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
Pawel Wawrzynski
IPOM
2007
Springer
14 years 2 months ago
Cognitive Network Management with Reinforcement Learning for Wireless Mesh Networks
We present a framework of cognitive network management by means of an autonomic reconfiguration scheme. We propose a network architecture that enables intelligent services to meet ...
Minsoo Lee, Dan Marconett, Xiaohui Ye, S. J. Ben Y...
ILP
2005
Springer
14 years 1 months ago
Guiding Inference Through Relational Reinforcement Learning
Abstract. Reasoning plays a central role in intelligent systems that operate in complex situations that involve time constraints. In this paper, we present the Adaptive Logic Inter...
Nima Asgharbeygi, Negin Nejati, Pat Langley, Sachi...
ATAL
2004
Springer
14 years 1 months ago
Bayesian Reinforcement Learning for Coalition Formation under Uncertainty
Research on coalition formation usually assumes the values of potential coalitions to be known with certainty. Furthermore, settings in which agents lack sufficient knowledge of ...
Georgios Chalkiadakis, Craig Boutilier