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Thirteen years have passed since Karl Sims published his work on evolving virtual creatures. Since then,several novel approaches to neural network evolution and genetic algorithms have been proposed. The aim of our work is to apply recent results in these ...
We consider the numerical optimization of dynamic molecular alignment by shaped femtosecond pulses, and study the scalability of the electric field subject to optimization by Evolution Strategies.The trade-off between fine-tuning of the electric field ...
Traditional parametric methods have limited success in estimating and forecasting the volatility of financial securities. Recent advance in evolutionary computation has provided additional tools to conduct data mining effectively. The current work ...
Kernel methods are mathematical tools that provide higher dimensional representation of given data set in feature space for pattern recognition and data analysis problems. Optimal Component Analysis (OCA) [4] poses the problem of finding an optimal ...
We have developed a real world application that models a financial futures market. The agent-based simulation includes speculator agents each of which uses a Genetic Algorithm (GA) to improve its profitability in the market. This is a realistic ...
This work aims at optimizing injection networks, which consist in adding a set of long-range links (called bypass links) in mobile multi-hop ad hoc networks so as to improve connectivity and overcome network partitioning. To this end, we rely on small-...
Stock selection for hedge fund portfolios is a challenging problem for Genetic Programming (GP) because the markets (the environment in which the GP solution must survive) are dynamic, unpredictable and unforgiving. How can GP be improved so that ...
Stock selection for hedge fund portfolios is a challenging problem for Genetic Programming (GP) because the markets (the environment in which the GP solution must survive) are dynamic, unpredictable and unforgiving. How can GP be improved so that ...
This paper proposes a novel application of differential evolution to solve a difficult dynamic optimisation or optimal control problem. The miss distance in a missile-target engagement is minimised using differential evolution. The difficulty of solving ...
This paper describes the application of evolutionary search to the problem of Flash memory wear-out. The operating parameters of Flash memory are notoriously difficult to determine, as the optimal values vary from batch to batch. These parameters are ...
Government, commercial, scientific, and defense applications inimage processing often require transmission of large amounts of data across bandwidth-limited channels. Applications require robust transforms simultaneously minimizing bandwidth ...
Credit institutions are seldom faced with problems dealing with single objectives. Often, decisions involving optimizing two or more competing goals simultaneously need to be made, and conventional optimization routines and models are incapable of ...
We have developed a technique to characterize software developers- styles using a set of source code metrics. This style fingerprint can be used to identify the likely author of a piece of code from a pool of candidates. Author identification has ...
This paper revisits the evolution of a neural controller for asimulated Personal Satellite Assistant (PSA) using the En-forced Sub-Populations (ESP) neuroevolutionary algorithm, as described by Sit et al. in 2005 [8].ESP has previously been shown to be ...
The task of reasoning with fuzzy description logics with fuzzy quantification is approached by means of an evolutionary algorithm. An essential ingredient of the proposed method is a heuristic, implemented as an intelligent mutation operator, which ...
This paper presents an approach to analyse the behaviours of teams of autonomous agents who work together to achieve a common goal. The agents in a team are evolved together using a genetic programming (GP) [8] approach where each team of agents is ...
This paper presents an evolutionary algorithm for modeling the arrival dates of document streams, which is any time-stamped collection of documents, such as newscasts, e-mails, scientific journals archives and weblog postings. The goal is to find a ...
This paper introduces a new variety of learning classifier system (LCS), called MILCS, with mutual information fitness.