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» A k-NN Based Perception Scheme for Reinforcement Learning
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ATAL
2007
Springer
13 years 12 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone
IPOM
2007
Springer
13 years 12 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...
ESANN
2008
13 years 7 months ago
Safe exploration for reinforcement learning
In this paper we define and address the problem of safe exploration in the context of reinforcement learning. Our notion of safety is concerned with states or transitions that can ...
Alexander Hans, Daniel Schneegaß, Anton Maxi...
BICA
2010
13 years 24 days ago
Application Feedback in Guiding a Deep-Layered Perception Model
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
Itamar Arel, Shay Berant
CAMP
2005
IEEE
13 years 11 months ago
Reinforcement Learning for P2P Searching
— For a peer-to-peer (P2P) system holding massive amount of data, an efficient and scalable search for resource sharing is a key determinant to its practical usage. Unstructured...
Luca Gatani, Giuseppe Lo Re, Alfonso Urso, Salvato...