Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation最新文献_第6页

Evolution under partial information 部分信息下的进化

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598375

D. Dang, P. Lehre

{"title":"Evolution under partial information","authors":"D. Dang, P. Lehre","doi":"10.1145/2576768.2598375","DOIUrl":"https://doi.org/10.1145/2576768.2598375","url":null,"abstract":"Complete and accurate information about the quality of candidate solutions is not always available in real-world optimisation. It is often prohibitively expensive to evaluate candidate solution on more than a few test cases, or the evaluation mechanism itself is unreliable. While evolutionary algorithms are popular methods in optimisation, the theoretical understanding is lacking for the case of partial information. This paper initiates runtime analysis of evolutionary algorithms where only partial information about fitness is available. Two scenarios are investigated. In partial evaluation of solutions, only a small amount of information about the problem is revealed in each fitness evaluation. We formulate a model that makes this scenario concrete for pseudo-Boolean optimisation. In partial evaluation of populations, only a few individuals in the population are evaluated, and the fitness values of the other individuals are missing or incorrect. For both scenarios, we prove that given a set of specific conditions, non-elitist evolutionary algorithms can optimise many functions in expected polynomial time even when vanishingly little information available. The conditions imply a small enough mutation rate and a large enough population size. The latter emphasises the importance of populations in evolution.","PeriodicalId":123241,"journal":{"name":"Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123700733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Evolving QWOP gaits 进化的QWOP步态

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598248

S. Ray, Vahl Scott Gordon, L. Vaucher

{"title":"Evolving QWOP gaits","authors":"S. Ray, Vahl Scott Gordon, L. Vaucher","doi":"10.1145/2576768.2598248","DOIUrl":"https://doi.org/10.1145/2576768.2598248","url":null,"abstract":"QWOP is a popular Flash game in which a human player controls a sprinter in a simulated 100-meter dash. The game is notoriously difficult owing to its ragdoll physics engine, and the simultaneous movements that must be carefully coordinated to achieve forward progress. While previous researchers have evolved gaits using simulations similar to QWOP, we describe a software interface that connects directly to QWOP itself, incorporating a genetic algorithm to evolve actual QWOP gaits. Since QWOP has no API, ours detects graphical screen elements and uses them to build a fitness function. Two variable-length encoding schemes, that codify sequences of QWOP control commands that loop to form gaits, are tested. We then compare the performance of SGA, Genitor, and a Cellular Genetic Algorithm on this task. Using only the end score as the basis for fitness, the cellular algorithm is consistently able to evolve a successful scooting strategy similar to one most humans employ. The results confirm that steady-state GAs are preferred when the task is sensitive to small input variations. Although the limited feedback does not yet produce performance competitive with QWOP champions, it is the first autonomous software evolution of successful QWOP gaits.","PeriodicalId":123241,"journal":{"name":"Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121825997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Towards highly optimized cartesian genetic programming: from sequential via SIMD and thread to massive parallel implementation 走向高度优化的笛卡尔遗传规划:从顺序通过SIMD和线程到大规模并行实现

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598343

Radek Hrbacek, L. Sekanina

引用次数: 21

Asymmetric quadratic landscape approximation model 非对称二次景观近似模型

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598381

Alexandru-Adrian Tantar, Emilia Tantar, O. Schütze

引用次数: 2

Grammar-based genetic programming with dependence learning and bayesian network classifier 基于语法的遗传规划与依赖学习和贝叶斯网络分类器

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598256

Pak-Kan Wong, Leung-Yau Lo, M. Wong, K. Leung

引用次数: 9

Comparing search techniques for finding subtle higher order mutants 比较寻找微妙的高阶突变体的搜索技术

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598286

Elmahdi Omar, Sudipto Ghosh, L. D. Whitley

引用次数: 28

Virtual photography using multi-objective particle swarm optimization 基于多目标粒子群优化的虚拟摄影

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598210

W. Barry, B. Ross

引用次数: 6

The tradeoffs between data delivery ratio and energy costs in wireless sensor networks: a multi-objectiveevolutionary framework for protocol analysis 无线传感器网络中数据传输率与能量成本的权衡:协议分析的多目标进化框架

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598384

Doina Bucur, Giovanni Iacca, Giovanni Squillero, A. Tonda

{"title":"The tradeoffs between data delivery ratio and energy costs in wireless sensor networks: a multi-objectiveevolutionary framework for protocol analysis","authors":"Doina Bucur, Giovanni Iacca, Giovanni Squillero, A. Tonda","doi":"10.1145/2576768.2598384","DOIUrl":"https://doi.org/10.1145/2576768.2598384","url":null,"abstract":"Wireless sensor network (WSN) routing protocols, e.g., the Collection Tree Protocol (CTP), are designed to adapt in an ad-hoc fashion to the quality of the environment. WSNs thus have high internal dynamics and complex global behavior. Classical techniques for performance evaluation (such as testing or verification) fail to uncover the cases of extreme behavior which are most interesting to designers. We contribute a practical framework for performance evaluation of WSN protocols. The framework is based on multi-objective optimization, coupled with protocol simulation and evaluation of performance factors. For evaluation, we consider the two crucial functional and non-functional performance factors of a WSN, respectively: the ratio of data delivery from the network (DDR), and the total energy expenditure of the network (COST). We are able to discover network topological configurations over which CTP has unexpectedly low DDR and/or high COST performance, and expose full Pareto fronts which show what the possible performance tradeoffs for CTP are in terms of these two performance factors. Eventually, Pareto fronts allow us to bound the state space of the WSN, a fact which provides essential knowledge to WSN protocol designers.","PeriodicalId":123241,"journal":{"name":"Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132256747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Applying GA with local search by taking hamming distances into consideration to credit erasure processing problems 将考虑汉明距离的局部搜索遗传算法应用于信用擦除处理问题

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598229

Yuji Sato, Yusuke Oku, Masanori Fukuda

{"title":"Applying GA with local search by taking hamming distances into consideration to credit erasure processing problems","authors":"Yuji Sato, Yusuke Oku, Masanori Fukuda","doi":"10.1145/2576768.2598229","DOIUrl":"https://doi.org/10.1145/2576768.2598229","url":null,"abstract":"Credit erasure processing refers to the process of canceling corresponding items from a list of accounts receivable by checking against a detailed statement when receiving accounts receivable and other payments. In credit erasure processing, it is sometimes necessary to perform the laborious task of searching for credited items based solely on billing data and payments received. In this paper, we define credit erasure processing as a large-scale subset sum problem, and propose a solution based on a genetic algorithm (GA). In particular, we propose improving the search precision by incorporating a local search method that takes Hamming distances into consideration. To this end, we compare the standard GA with the result of adding a simple local search to the standard GA. This is done using a set of data where the numbers of digits in the billed quantities are roughly the same, another set of data where the numbers of digits are more varied, and a set of real data. As a result, we show that the proposed method works effectively when the numbers of digits in the billed quantities are roughly the same or when the fitness score is has a somewhat higher value.","PeriodicalId":123241,"journal":{"name":"Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132395519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Three-cornered coevolution learning classifier systems for classification tasks 面向分类任务的三角协同进化学习分类器系统

Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI: 10.1145/2576768.2598235

S. Marzukhi, Will N. Browne, Mengjie Zhang

{"title":"Three-cornered coevolution learning classifier systems for classification tasks","authors":"S. Marzukhi, Will N. Browne, Mengjie Zhang","doi":"10.1145/2576768.2598235","DOIUrl":"https://doi.org/10.1145/2576768.2598235","url":null,"abstract":"The Three-Cornered Coevolution concept describes a framework where artificial problems may be generated in concert with classification agents in order to provide insight into their relationships. This is unlike standard studies where humans set a problem's difficulty, which may have bias or lack understanding of the multiple interactions of a problem's characteristics, such as noise in conjunction with class imbalance. Previous studies have shown that it is feasible to generate problems with one agent in relation to a single classification agent's performance, but when to adjust the problem difficulty was manually set. This paper introduces a second classification agent to trigger the coevolutionary process within the system, where its functionality and effect on the system requires investigation. The classification agents, in this case Learning Classifier Systems, use different styles of learning techniques (e.g. supervised or reinforcement learning techniques) to learn the problems. Experiments show that the realized system is capable of autonomously generating various problems, triggering learning and providing insight into each learning system's ability by determining the problem domains where they perform relatively well - this is in contrast to humans having to determine the problem domains.","PeriodicalId":123241,"journal":{"name":"Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114219457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2