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ICML
2006
IEEE
16 years 7 months ago
PAC model-free reinforcement learning
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...
ICALP
2009
Springer
16 years 6 months ago
Rate-Based Transition Systems for Stochastic Process Calculi
A variant of Rate Transition Systems (RTS), proposed by Klin and Sassone, is introduced and used as the basic model for defining stochastic behaviour of processes. The transition r...
Rocco De Nicola, Diego Latella, Michele Loreti, Mi...
PERCOM
2004
ACM
16 years 5 months ago
Modelling and Using Imperfect Context Information
Most recently developed context-aware software applications make unrealistic assumptions about the quality of the available context information, which can lead to inappropriate ac...
Karen Henricksen, Jadwiga Indulska
BSN
2009
IEEE
140views Sensor Networks» more  BSN 2009»
16 years 1 months ago
A Distributed Hidden Markov Model for Fine-grained Annotation in Body Sensor Networks
—Human movement models often divide movements into parts. In walking the stride can be segmented into four different parts, and in golf and other sports, the swing is divided int...
Eric Guenterberg, Hassan Ghasemzadeh, Roozbeh Jafa...
AFRICACRYPT
2009
Springer
16 years 1 months ago
Unifying Zero-Knowledge Proofs of Knowledge
Abstract. We present a simple zero-knowledge proof of knowledge protocol of which many protocols in the literature are instantiations. These include Schnorr’s protocol for provin...
Ueli M. Maurer