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ICML
1996
IEEE
15 years 10 months ago
Learning Evaluation Functions for Large Acyclic Domains
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Justin A. Boyan, Andrew W. Moore
BMCBI
2006
123views more  BMCBI 2006»
14 years 9 months ago
Computational models with thermodynamic and composition features improve siRNA design
Background: Small interfering RNAs (siRNAs) have become an important tool in cell and molecular biology. Reliable design of siRNA molecules is essential for the needs of large fun...
Svetlana A. Shabalina, Alexey N. Spiridonov, Aleks...
ATAL
2009
Springer
15 years 4 months ago
Integrating organizational control into multi-agent learning
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
GECCO
2009
Springer
152views Optimization» more  GECCO 2009»
15 years 4 months ago
Application of evolutionary algorithms in detection of SIP based flooding attacks
The Session Initiation Protocol (SIP) is the de facto standard for user’s session control in the next generation Voice over Internet Protocol (VoIP) networks based on the IP Mul...
M. Ali Akbar, Muddassar Farooq
GECCO
2005
Springer
149views Optimization» more  GECCO 2005»
15 years 3 months ago
There's more to a model than code: understanding and formalizing in silico modeling experience
Mapping biology into computation has both a domain specific aspect – biological theory – and a methodological aspect – model development. Computational modelers have implici...
Janet Wiles, Nicholas Geard, James Watson, Kai Wil...
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