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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 1 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
GLVLSI
2009
IEEE
146views VLSI» more  GLVLSI 2009»
15 years 1 months ago
A reconfigurable stochastic architecture for highly reliable computing
Mounting concerns over variability, defects and noise motivate a new approach for integrated circuits: the design of stochastic logic, that is to say, digital circuitry that opera...
Xin Li, Weikang Qian, Marc D. Riedel, Kia Bazargan...
ATAL
2006
Springer
15 years 1 months ago
Behaviosites: a novel paradigm for affecting distributed behavior
In this paper we present the Behaviosite paradigm, a new approach to affecting the behavior of distributed agents in a multiagent system, which is inspired by biological parasites ...
Amit Shabtay, Zinovi Rabinovich, Jeffrey S. Rosens...
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 1 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
GECCO
2006
Springer
170views Optimization» more  GECCO 2006»
15 years 1 months ago
Combining simplex with niche-based evolutionary computation for job-shop scheduling
We propose a hybrid algorithm (called ALPINE) between Genetic Algorithm and Dantzig's Simplex method to approximate optimal solutions for the Flexible Job-Shop Problem. Local...
Syhlin Kuah, Joc Cing Tay