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Evolving digital circuits using multi expression programming
Proceedings. 2004 NASA/DoD Conference on Evolvable Hardware, 2004., 2004Multi expression programming (MEP) is a genetic programming (GP) variant that uses linear chromosomes for solution encoding. A unique MEP feature is its ability of encoding multiple solutions of a problem in a single chromosome. These solutions are handled in the same time complexity as other techniques that encode a single solution in a chromosome. In
M. Oltean, C. Grosan
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Multi-Agent Cooperative Pursuit-Evasion Control Using Gene Expression Programming
IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 2021This paper works on multiple-pursuer single-evader (MPSE) problems with a fast evader, which means multiple pursuers try to capture one evader while the evader tries to escape from the encirclement. The biggest concern is that the maximum velocity of the evader is larger than all the pursuers.
Yinjie Ni +5 more
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MREP: Multi-Reference Expression Programming
2016MEP is a variant of genetic program applied to solve the symbol regression and classification problems. It can encode multiple solutions of a problem in a single chromosome. However, when the ratio of genes reuse is low, it may not get a high accuracy result within limited iterations and may fall into the trap of local optimum. Therefore, we proposed a
Qingke Zhang +3 more
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Image retrieval based on Multi Expression Programming algorithms
2013 Ninth International Conference on Natural Computation (ICNC), 2013The effectiveness of content-based image retrieval (CBIR) systems can be improved by combining image features or by weighting image similarities, as computed from multiple feature vectors. However, feature combination does not always make sense and the combined similarity function can be more complex than weight-based functions to better satisfy the ...
Weihong Wang, Wenrou Lin, Qu Li
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Adaptive Multi‐phenotype Based Gene Expression Programming Algorithm
Chinese Journal of Electronics, 2016Expression theory is the mathematical foundation of evolutionary computation. In order to investigate the problems in Gene expression programming (GEP) expression theory, we clarified the difference between genotypic expression space and phenotypic expression space. We also presented phenotypic expression space definition and theory.
Qu Li, Hongbing Cheng, Min Yao
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Multi-label Classification with Gene Expression Programming
2009In this paper, we introduce a Gene Expression Programming algorithm for multi label classification. This algorithm encodes each individual into a discriminant function that shows whether a pattern belongs to a given class or not. The algorithm also applies a niching technique to guarantee that the population includes functions for each existing class ...
J. L. Ávila, E. L. Gibaja, S. Ventura
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Multi-objective Classification Rule Mining Using Gene Expression Programming
2008 Third International Conference on Convergence and Hybrid Information Technology, 2008In this paper, the classification rule-mining problem is considered as a multi-objective problem rather than a uni-objective one. Metrics like predictive accuracy and comprehensibility, used for evaluating a rule can be thought of as different criteria of this problem.
Satchidananda Dehuri, Sung-Bae Cho
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New Ground-Motion Prediction Equations Using Multi Expression Programing
Journal of Earthquake Engineering, 2011High-precision attenuation models were derived to estimate peak ground acceleration (PGA), velocity (PGV), and displacement (PGD) using a new variant of genetic programming, namely multi expression programming (MEP). The models were established based on an extensive database of ground-motion recordings released by Pacific Earthquake Engineering ...
Amir Hossein Alavi +3 more
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A gene expression programming method for multi-target regression
Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, 2018The study of problems that involve data examples associated with multiple targets at the same time has gained a lot of attention in the past few years. In this work, a method based on gene expression programming for the multi-target regression problem is proposed.
Oscar Reyes +3 more
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Improving Multi Expression Programming Using Reuse-Based Evaluation
2012Multi expression programming is a linear genetic programming that dynamically determines its output from a series of genes of the chromosome. It works on a fixed-length individual, but gives rise to the complexity of the decoding process and fitness computations.
Wei Deng, Pei He
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