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CEC
2009
IEEE
10 years 9 months ago
Self modifying Cartesian Genetic Programming: Parity
— Self Modifying CGP (SMCGP) is a developmental form of Cartesian Genetic Programming(CGP). It differs from CGP by including primitive functions which modify the program. Beginni...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
CEC
2009
IEEE
10 years 9 months ago
Modeling multi-agent labor market based on co-evolutionary computation and game theory
— In a real-world, labor market consist of employer and employee, and these individuals form relationship through mutual interactions. This paper mainly focuses on development of...
Hee-Taek Kim, Sung-Bae Cho
CEC
2009
IEEE
10 years 9 months ago
Coevolution of language and intentionality sharing
—We conduct an evolutionary simulation to explore the coevolution of language and a language-related ability, intentionality sharing. Our simulation shows that during the evoluti...
Tao Gong, James W. Minett, William S.-Y. Wang
CEC
2009
IEEE
10 years 9 months ago
Robot path planning in uncertain environments based on particle swarm optimization
— We propose a robot path planning method based on particle swarm optimization in an uncertain environment. We consider the case that a robot’s cognition to its environment is ...
Dunwei Gong, Li Lu, Ming Li
CEC
2009
IEEE
10 years 9 months ago
Lamarckian neuroevolution for visual control in the Quake II environment
Abstract— A combination of backpropagation and neuroevolution is used to train a neural network visual controller for agents in the Quake II environment. The agents must learn to...
Matt Parker, Bobby D. Bryant
CEC
2009
IEEE
10 years 9 months ago
Comparing parameter tuning methods for evolutionary algorithms
Abstract— Tuning the parameters of an evolutionary algorithm (EA) to a given problem at hand is essential for good algorithm performance. Optimizing parameter values is, however,...
Selmar K. Smit, A. E. Eiben
CEC
2009
IEEE
10 years 9 months ago
A micro-bacterial foraging algorithm for high-dimensional optimization
- Very recently bacterial foraging has emerged as a powerful technique for solving optimization problems. In this paper, we introduce a micro-bacterial foraging optimization algori...
Sambarta Dasgupta, Arijit Biswas, Swagatam Das, Bi...
CEC
2009
IEEE
10 years 9 months ago
Dispatching rules for production scheduling: A hyper-heuristic landscape analysis
— Hyper-heuristics or “heuristics to chose heuristics” are an emergent search methodology that seeks to automate the process of selecting or combining simpler heuristics in o...
Gabriela Ochoa, José Antonio Vázquez...
CEC
2009
IEEE
10 years 9 months ago
Structure learning and optimisation in a Markov-network based estimation of distribution algorithm
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...
Alexander E. I. Brownlee, John A. W. McCall, Siddh...
CEC
2009
IEEE
10 years 9 months ago
Dynamic search initialisation strategies for multi-objective optimisation in peer-to-peer networks
Abstract— Peer-to-peer based distributed computing environments can be expected to be dynamic to greater of lesser degree. While node losses will not usually lead to catastrophic...
Ian Scriven, Andrew Lewis, Sanaz Mostaghim
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