Niching genetic network programming with rule accumulation for decision making: An evolutionary rule-based approach

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@Article{DBLP:journals/eswa/LiYW18,

• author = "Xianneng Li and Meihua Yang and Shizhe Wu",
• title = "Niching genetic network programming with rule accumulation for decision making: An evolutionary rule-based approach",
• journal = "Expert Systems with Applications",
• volume = "114",
• pages = "374--387",
• year = "2018",
• month = "30 " # dec,
• keywords = "genetic algorithms, genetic programming, Decision making, Genetic network programming, Learning classifier system, Niching, Reinforcement learning, Rule accumulation",
• ISSN = "0957-4174",
• URL = "https://doi.org/10.1016/j.eswa.2018.07.041",
• DOI = "doi:10.1016/j.eswa.2018.07.041",
• timestamp = "Tue, 28 Aug 2018 01:00:00 +0200",
• biburl = "https://dblp.org/rec/journals/eswa/LiYW18.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• size = "14 pages",
• abstract = "As one of the most important research branches of evolutionary computation (EC), learning classifier system (LCS) is dedicated to discover decision making classifiers (IF-THEN type rules) via evolution and learning. Recent advances in LCS have shown distinguished generalization property over traditional approaches. In this paper, a novel LCS named niching genetic network programming with rule accumulation (nGNP-RA) is proposed. The unique features of the proposal arise from the following three points: First, it uses an advanced graph-based EC named GNP as the rule generator, resulting higher knowledge representation ability than traditional genetic algorithm (GA)-based LCSs; Second, a novel niching mechanism is developed in GNP to encourage the discovery of high-quality diverse rules; Third, a novel reinforcement learning (RL)-based mechanism is embedded to assign accurate credits to the discovered rules. To verify the effectiveness and robustness of nGNP-RA over traditional systems, two decision making testbeds are applied, including the benchmark tileworld problem and the real mobile robot control application.",
• notes = "Faculty of Management and Economics, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi, Dalian 116024, China",

}

Genetic Programming entries for Xianneng Li Meihua Yang Shizhe Wu

Citations