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» On the Convergence of Bound Optimization Algorithms
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CDC
2010
IEEE
182views Control Systems» more  CDC 2010»
14 years 11 months ago
An approximate dual subgradient algorithm for multi-agent non-convex optimization
We consider a multi-agent optimization problem where agents aim to cooperatively minimize a sum of local objective functions subject to a global inequality constraint and a global ...
Minghui Zhu, Sonia Martínez
143
Voted
GECCO
2003
Springer
15 years 9 months ago
HEMO: A Sustainable Multi-objective Evolutionary Optimization Framework
The capability of multi-objective evolutionary algorithms (MOEAs) to handle premature convergence is critically important when applied to real-world problems. Their highly multi-mo...
Jianjun Hu, Kisung Seo, Zhun Fan, Ronald C. Rosenb...
TEC
2002
128views more  TEC 2002»
15 years 3 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
ICONIP
2004
15 years 5 months ago
Neural-Evolutionary Learning in a Bounded Rationality Scenario
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
Ricardo Matsumura de Araújo, Luís C....
UAI
2004
15 years 5 months ago
Heuristic Search Value Iteration for POMDPs
We present a novel POMDP planning algorithm called heuristic search value iteration (HSVI). HSVI is an anytime algorithm that returns a policy and a provable bound on its regret w...
Trey Smith, Reid G. Simmons