Using habituation as a simple and fundamental learning mechanism in an embodied artificial agent

IF 1.2 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Adaptive Behavior Pub Date : 2022-10-10 DOI:10.1177/10597123221116183

Tristan Gillard, J. Fix, A. Dutech

引用次数: 0

Abstract

Habituation, a non-associative learning widely observed across phylogeny, is fundamental for adaptation and, thus, survival of living organisms. This paper investigates the main characteristics of habituation in order to present three new computational models inspired by habituation. We develop these models as part of the Iterant Deformable Sensorimotor Medium (IDSM), a recently developed abstract model of behavior formation. The characteristics of these models are studied and analyzed. Our long-term objective is to research new unsupervised learning mechanisms for artificial learning agents.

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在具体的人工智能体中使用习惯化作为一种简单而基本的学习机制

习惯化是一种在系统发育学中广泛观察到的非联想学习，是生物体适应和生存的基础。本文研究了习惯化的主要特征，以期提出三个受习惯化启发的新的计算模型。我们将这些模型作为迭代变形感觉运动介质（IDSM）的一部分进行开发，IDSM是一种最近开发的行为形成抽象模型。对这些模型的特点进行了研究和分析。我们的长期目标是为人工学习代理研究新的无监督学习机制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Adaptive Behavior 工程技术-计算机：人工智能

CiteScore

4.30

自引率

18.80%

发文量

审稿时长

>12 weeks

期刊介绍： _Adaptive Behavior_ publishes articles on adaptive behaviour in living organisms and autonomous artificial systems. The official journal of the _International Society of Adaptive Behavior_, _Adaptive Behavior_, addresses topics such as perception and motor control, embodied cognition, learning and evolution, neural mechanisms, artificial intelligence, behavioral sequences, motivation and emotion, characterization of environments, decision making, collective and social behavior, navigation, foraging, communication and signalling. Print ISSN: 1059-7123