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CP
2004
Springer
14 years 26 days ago
Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
Vincent A. Cicirello, Stephen F. Smith
IJCAI
2001
13 years 8 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
ENTCS
2007
83views more  ENTCS 2007»
13 years 7 months ago
Enhancing Theorem Prover Interfaces with Program Slice Information
This paper proposes an extension to theorem proving interfaces for use with proofdirected debugging and other disproof-based applications. The extension is based around tracking a...
Louise A. Dennis
VTC
2008
IEEE
127views Communications» more  VTC 2008»
14 years 1 months ago
Performance Evaluation of Joint FEC and ARQ Optimization Heuristic Algorithms under Gilbert-Elliot Wireless Channel
— In this paper, we evaluate the performance of adaptive algorithms for selecting the number of redundant packets by jointly considering the forward error correction (FEC) and au...
Azfar Moid, Abraham O. Fapojuwo
RTCSA
2006
IEEE
14 years 1 months ago
Maximizing Guaranteed QoS in (m, k)-firm Real-time Systems
(m,k)-firm constraints have been used to schedule tasks in soft/firm real-time systems under overloaded conditions. In general, they are provided by application designers to guara...
Jian (Denny) Lin, Albert M. K. Cheng