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Evolutionary computation for modeling and optimization. (2006)

by D Ashlock
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Adaptive Computational Chemotaxis in Bacterial Foraging Optimization: An Analysis

by Sambarta Dasgupta, Arijit Biswas, Ajith Abraham, Swagatam Das - IEEE Computer Society Press, ISBN 0-7695-3109-1 , 2008
"... Some researchers have illustrated how individual and groups of bacteria forage for nutrients and to model it as a distributed optimization process, which is called the Bacterial Foraging Optimization (BFOA). One of the major driving forces of BFOA is the chemotactic movement of a virtual bacterium, ..."
Abstract - Cited by 23 (6 self) - Add to MetaCart
Some researchers have illustrated how individual and groups of bacteria forage for nutrients and to model it as a distributed optimization process, which is called the Bacterial Foraging Optimization (BFOA). One of the major driving forces of BFOA is the chemotactic movement of a virtual bacterium, which models a trial solution of the optimization problem. In this article, we analyze the chemotactic step of a one dimensional BFOA in the light of the classical Gradient Descent Algorithm (GDA). Our analysis points out that chemotaxis employed in BFOA may result in sustained oscillation, especially for a flat fitness landscape, when a bacterium cell is very near to the optima. To accelerate the convergence speed near optima we have made the chemotactic step size C adaptive. Computer simulations over several numerical benchmarks indicate that BFOA with the new chemotactic operation shows better convergence behavior as compared to the classical BFOA.
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... was allowed to decrease linearly from 2.4 to 0.35. Finally, ⇀ V max was set at ⃗Xmax. 3) Real-Coded GA: In this research, we used a standard real-coded GA (also known as evolutionary algorithm or EA =-=[47]-=-) that was previously found to work well on real-world problems [48]. The EA works as follows: First, all individuals are randomly initialized and evaluated according to a given objective function. Af...

Satisfiability of Non-linear (Ir)rational Arithmetic

by Harald Zankl, Aart Middeldorp - 16th International Conference on Logic for Programming, Artificial Intelligence and Reasoning, LPAR’10 , 2010
"... Abstract. We present a novel way for reasoning about (possibly ir)ratio-nal quantifier-free non-linear arithmetic by a reduction to SAT/SMT. The approach is incomplete and dedicated to satisfiable instances only but is able to produce models for satisfiable problems quickly. These char-acteristics s ..."
Abstract - Cited by 10 (1 self) - Add to MetaCart
Abstract. We present a novel way for reasoning about (possibly ir)ratio-nal quantifier-free non-linear arithmetic by a reduction to SAT/SMT. The approach is incomplete and dedicated to satisfiable instances only but is able to produce models for satisfiable problems quickly. These char-acteristics suffice for applications such as termination analysis of rewrite systems. Our prototype implementation, called MiniSmt, is made freely available. Extensive experiments show that it outperforms current SMT solvers especially on rational and irrational domains.
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... we discuss related work on matrix interpretations. An extension to rational domains was already proposed in 2007 [16] (for termination proofs of string rewrite systems) where evolutionary algorithms =-=[3]-=- were suggested to find suitable rational coefficients. However, no benchmarks are given there that show a gain in power. In [15] polynomial interpretations are extended to rational coefficients. This...

Embodied artificial evolution Artificial evolutionary systems in the 21st Century

by A. E. Eiben, S. Kernbach, Evert Haasdijk, A. E. Eiben, E. Haasdijk, E. Haasdijk, S. Kernbach
"... Ó The Author(s) 2012. This article is published with open access at Springerlink.com Abstract Evolution is one of the major omnipresent powers in the universe that has been studied for about two centuries. Recent scientific and technical developments make it possible to make the transition from pass ..."
Abstract - Cited by 6 (4 self) - Add to MetaCart
Ó The Author(s) 2012. This article is published with open access at Springerlink.com Abstract Evolution is one of the major omnipresent powers in the universe that has been studied for about two centuries. Recent scientific and technical developments make it possible to make the transition from passively understanding to actively using evolutionary processes. Today this is possible in Evolutionary Computing, where human experimenters can design and manipulate all components of evolutionary processes in digital spaces. We argue that in the near future it will be possible to implement artificial evolutionary processes outside such imaginary spaces and make them physically embodied. In other words, we envision the ‘‘Evolution of Things’’, rather than just the evolution of digital objects, leading to a new field of Embodied Artificial Evolution (EAE). The main objective of this paper is to present a unifying vision in order to aid the development of this high potential research area. To this end, we introduce the notion of EAE, discuss a few examples and applications, and elaborate on the expected benefits as well as the grand challenges this developing field will have to address.
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...nd the result are both digital. Well known areas in this category are evolutionary optimisation, evolutionary data modeling and evolutionary simulations in artificial life, evolutionary economy, etc. =-=[4, 35, 60]-=-. In the second kind, the evolutionary process is digital, but the result of evolution (e.g., the blueprint of a chair or an antenna) is made physical by an extra construction step afterwards. This is...

An Improved Harmony Search Algorithm with Differential Mutation Operator

by Prithwish Chakraborty, Gourab Ghosh Roy, Swagatam Das, Dhaval Jain, Ajith Abraham , 2009
"... Harmony Search (HS) is a recently developed stochastic algorithm which imitates the music improvisation process. In this process, the musicians improvise their instrument pitches searching for the perfect state of harmony. Practical experiences, however, suggest that the algorithm suffers from the ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
Harmony Search (HS) is a recently developed stochastic algorithm which imitates the music improvisation process. In this process, the musicians improvise their instrument pitches searching for the perfect state of harmony. Practical experiences, however, suggest that the algorithm suffers from the problems of slow and/or premature convergence over multimodal and rough fitness landscapes. This paper presents an attempt to improve the search performance of HS by hybridizing it with Differential Evolution (DE) algorithm. The performance of the resulting hybrid algorithm has been compared with classical HS, the global best HS, and a very popular variant of DE over a test-suite of six well known benchmark functions and one interesting practical optimization problem. The comparison is based on the following performance indices- (i) accuracy of final result, (ii) computational speed, and (iii) frequency of hitting the optima.

Evolution In Materio

by Simon Harding , 2005
"... This thesis describes a method to program materials directly to perform a computation. The work demonstrates that an evolutionary algorithm can exploit the physical properties of materials such as liquid crystal, enabling them to perform computation. The thesis demonstrates the approach applied to s ..."
Abstract - Cited by 5 (4 self) - Add to MetaCart
This thesis describes a method to program materials directly to perform a computation. The work demonstrates that an evolutionary algorithm can exploit the physical properties of materials such as liquid crystal, enabling them to perform computation. The thesis demonstrates the approach applied to several different problems including signal processing, control and digital logic. In addition to demonstrating the technique on real liquid crystal, simulations are used to show the applicability to cellular automata and a kind of neural network. The thesis also argues that the developed technique may also be suitable for programming systems, such as, bacterial consortia to perform computations.

AnMDL approach to efficiently discover communities in bipartite network

by Kaikuo Xu, Changjie Tang, Chuan Li, Yexi Jiang, Rong Tang - in Database Systems for Advanced Applications
"... Abstract. Bipartite network is a branch of complex network. It is widely used in many applications such as social network analysis, collaborative filtering and information retrieval. Partitioning a bipartite network into smaller modules helps to get insight of the structure of the bipartite network. ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
Abstract. Bipartite network is a branch of complex network. It is widely used in many applications such as social network analysis, collaborative filtering and information retrieval. Partitioning a bipartite network into smaller modules helps to get insight of the structure of the bipartite network. The main contributions of this paper include: (1) proposing an MDL 21 criterion for identifying a good partition of a bipartite network. (2) presenting a greedy algorithm based on combination theory, named as MDL-greedy, to approach the optimal partition of a bipartite network. The greedy algorithm automatically searches for the number of partitions, and requires no user intervention. (3) conducting experiments on synthetic datasets and the southern women dataset. The results show that our method generates higher quality results than the state-of-art methods Cross-Association and Information-theoretic co-clustering. Experiment results also show the good scalability of the proposed algorithm. The highest improvement could be up to about 14 % for the precision, 40 % for the ratio and 70 % for the running time.
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... Qc* and T(A; k*, e*, Qr*, Qc*).sTypically, this problem is a combination optimization problem, thus is a NP-hard problem [22].sA common approach to conquer such problem is the evolutionary algorithm =-=[23, 24]-=-. In ordersto obtain a deterministic result, we use an approximate algorithm instead.s4 A split-refine greedy algorithms4.1 Sketch of the algorithmsThe proposed algorithm is a greedy algorithm, as sho...

The Graph Crossing Number and its Variants: A Survey

by Marcus Schaefer , 2013
"... The crossing number is a popular tool in graph drawing and visualization, but there is not really just one crossing number; there is a large family of crossing number notions of which the crossing number is the best known. We survey the rich variety of crossing number variants that have been introdu ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
The crossing number is a popular tool in graph drawing and visualization, but there is not really just one crossing number; there is a large family of crossing number notions of which the crossing number is the best known. We survey the rich variety of crossing number variants that have been introduced in the literature for purposes that range from studying the theoretical underpinnings of the crossing number to crossing minimization for visualization problems.
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...rary graphs also defined rectilinear crossing number [148]. 5Recent examples defining crossing number as pcr include textbooks in combinatorics [320, 312, 331], and books in algorithms and complexity =-=[28, 165, 25, 26]-=-. the electronic journal of combinatorics 20(2) (2013), #DS21 3Figure 1; swapping the arcs, or even just rerouting one of the arcs along the adjacent edge will lead to an increase in the pair crossin...

Dynamics of a public investment game: from nearest-neighbor lattices to small-world networks

by Roberto Da Silva, Ana L. C. Bazzan, Re T. Baraviera, Silvio R - Advances in Artificial Economics, The Economy as a Complex Dynamic System, number 584 in Lecture Notes in Economics and Mathematical Systems, chapter 16 , 2006
"... In the fields of complex systems and multiagent systems there is an extensive list of publications on nontrivial phenomena which arise due to the interplay between microscopic (individual) rules and macroscopic (group) behavior. In the context of socioeconomic behavior, this has been thoroughly disc ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
In the fields of complex systems and multiagent systems there is an extensive list of publications on nontrivial phenomena which arise due to the interplay between microscopic (individual) rules and macroscopic (group) behavior. In the context of socioeconomic behavior, this has been thoroughly discussed by Durlauf [2]. Within
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...opic (group) behavior. In the context of socioeconomic behavior, this has been thoroughly discussed by Durlauf [2]. Within this scenario we study here a variation of a simple “public investment game” =-=[1]-=-. In its original version, one wishes to model public spending on public goods. Players can invest their money in a common pool, and profits are equally distributed among all participants irrespective...

Single Parent Genetic Programming

by Wendy Ashlock, Roseheart Biomaths
"... The most controversial part of genetic programming is its highly disruptive and potentially innovative subtree crossover operator. The clearest problem with the crossover operator is its potential to induce defensive metaselection for large parse trees, a process usually termed “bloat. ” Single pare ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
The most controversial part of genetic programming is its highly disruptive and potentially innovative subtree crossover operator. The clearest problem with the crossover operator is its potential to induce defensive metaselection for large parse trees, a process usually termed “bloat. ” Single parent genetic programming is a form of genetic programming in which bloat is reduced by doing subtree crossover with a fixed population of ancestor trees. Analysis of mean tree size growth demonstrates that this fixed and limited set of crossover partners provides implicit, automatic control on tree size in the evolving population, reducing the need for additionally disruptive trimming of large trees. The choice of ancestor trees can also incorporate expert knowledge into the genetic programming system. The system is tested on four problems: plus-one-recall-store (PORS), odd parity, plus-times-half (PTH) and a bioinformatic model fitting problem (NIPs). The effectiveness of the technique varies with the problem and choice of ancestor set. At the extremes, improvements in time to solution in excess of 4700-fold were observed for the PORS problem, and no significant improvements for the PTH problem were observed. I.
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...blem case. It would also be interesting to test the single parent technique with other kinds of genetic programming like ISAc lists [2] or finite state automata or graph-based evolutionary algorithms =-=[4]-=-. It would be good to be able to categorize which sorts of problems work well with the single parent technique and which don’t. Single parent genetic programming could be used with competitive problem...

Multi-Agent Learning for

by Cheng Wu, Advisor Prof, Waleed Meleis - Control of Internet Traffic Routing”, Learning Systems for Control, IEE Seminar , 2000
"... ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
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... value function gives the expected accumulated and long-term value of an action under subsequent states. The concept of a value function distinguishes reinforcement learning from evolutionary methods =-=[9, 7, 15]-=-. Instead of directly searching the entire policy space by evolutionary evaluation, a value function evaluates an action’s desirability at the current state by accumulating delayed rewards. In reinfor...

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