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NECO
2007
150views more  NECO 2007»
13 years 6 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
IFM
2010
Springer
190views Formal Methods» more  IFM 2010»
13 years 5 months ago
On Model Checking Techniques for Randomized Distributed Systems
Abstract. The automata-based model checking approach for randomized distributed systems relies on an operational interleaving semantics of the system by means of a Markov decision ...
Christel Baier
QUESTA
2010
112views more  QUESTA 2010»
13 years 5 months ago
Admission control for a multi-server queue with abandonment
In a M/M/N+M queue, when there are many customers waiting, it may be preferable to reject a new arrival rather than risk that arrival later abandoning without receiving service. O...
Yasar Levent Koçaga, Amy R. Ward
BCB
2010
140views Bioinformatics» more  BCB 2010»
13 years 2 months ago
Guiding belief propagation using domain knowledge for protein-structure determination
A major bottleneck in high-throughput protein crystallography is producing protein-structure models from an electrondensity map. In previous work, we developed Acmi, a probabilist...
Ameet Soni, Craig A. Bingman, Jude W. Shavlik
IJRR
2011
218views more  IJRR 2011»
13 years 2 months ago
Motion planning under uncertainty for robotic tasks with long time horizons
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...