Self-Adaptation of Meta-Parameters for Lamarckian-Inherited Neuromodulated Neurocontrollers in the Pursuit-Evasion Game

Determining meta-parameter settings is a longstanding challenge in evolutionary computing, and often involves running repeated simulations with successive estimated values until acceptable values are found. The term metaevolution is often used to describe the optimization of one or more of the meta-...

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Bibliographic Details
Published in:	2020 IEEE Symposium Series on Computational Intelligence (SSCI) pp. 2592 - 2599
Main Authors:	Showalter, Ian, Schwartz, Howard
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2020
Subjects:	Evolutionary computation Evolutionary Meta-parameters Games Hebbian Learning Lamarckian Inheritance Multi-objective Neurocontrollers Neuroevolution Neuromodulation Optimization Parameter Control Parameter Tuning Pursuit-Evasion Sociology Statistics Unsupervised Learning
Online Access:	Get full text
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