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GECCO
2004
Springer
122views Optimization» more  GECCO 2004»
14 years 1 months ago
An Improved Diversity Mechanism for Solving Constrained Optimization Problems Using a Multimembered Evolution Strategy
This paper presents an improved version of a simple evolution strategy (SES) to solve global nonlinear optimization problems. As its previous version, the approach does not require...
Efrén Mezura-Montes, Carlos A. Coello Coell...
DMIN
2006
125views Data Mining» more  DMIN 2006»
13 years 9 months ago
Biomedical Hypothesis Generation and Testing by Evolutionary Computation
- Filtering the immense amount of data available electronically over the World Wide Web is an important task of search engines in data mining applications. Users when performing se...
Robert Kozma, Anna L. Buczak
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 2 months ago
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
Oliver Kramer, Bartek Gloger, Andreas Goebels
ML
1998
ACM
117views Machine Learning» more  ML 1998»
13 years 8 months ago
Learning Team Strategies: Soccer Case Studies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy, but may behave di erently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...
AAAI
2006
13 years 9 months ago
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Shimon Whiteson, Peter Stone