{"title":"耗散算术","authors":"W. Langdon","doi":"10.25088/complexsystems.31.3.287","DOIUrl":null,"url":null,"abstract":"Large arithmetic expressions are dissipative: they lose information and are robust to perturbations. Lack of conservation gives resilience to fluctuations. The limited precision of floating point and the mixture of linear and nonlinear operations make such functions anti-fragile and give a largely stable locally flat plateau a rich fitness landscape. This slows long-term evolution of complex programs, suggesting a need for depth-aware crossover and mutation operators in tree-based genetic programming. It also suggests that deeply nested computer program source code is error tolerant because disruptions tend to fail to propagate, and therefore the optimal placement of test oracles is as close to software defects as practical.","PeriodicalId":50871,"journal":{"name":"Advances in Complex Systems","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dissipative Arithmetic\",\"authors\":\"W. Langdon\",\"doi\":\"10.25088/complexsystems.31.3.287\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Large arithmetic expressions are dissipative: they lose information and are robust to perturbations. Lack of conservation gives resilience to fluctuations. The limited precision of floating point and the mixture of linear and nonlinear operations make such functions anti-fragile and give a largely stable locally flat plateau a rich fitness landscape. This slows long-term evolution of complex programs, suggesting a need for depth-aware crossover and mutation operators in tree-based genetic programming. It also suggests that deeply nested computer program source code is error tolerant because disruptions tend to fail to propagate, and therefore the optimal placement of test oracles is as close to software defects as practical.\",\"PeriodicalId\":50871,\"journal\":{\"name\":\"Advances in Complex Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Complex Systems\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.25088/complexsystems.31.3.287\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Complex Systems","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.25088/complexsystems.31.3.287","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Large arithmetic expressions are dissipative: they lose information and are robust to perturbations. Lack of conservation gives resilience to fluctuations. The limited precision of floating point and the mixture of linear and nonlinear operations make such functions anti-fragile and give a largely stable locally flat plateau a rich fitness landscape. This slows long-term evolution of complex programs, suggesting a need for depth-aware crossover and mutation operators in tree-based genetic programming. It also suggests that deeply nested computer program source code is error tolerant because disruptions tend to fail to propagate, and therefore the optimal placement of test oracles is as close to software defects as practical.
期刊介绍:
Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.