From Fly Detectors to Action Control: Representations in Reinforcement Learning

被引：0

作者：

Rusanen, Anna-Mari ^{[1
]}

Lappi, Otto ^{[1
]}

Pekkanen, Jami ^{[1
]}

Kuokkanen, Jesse ^{[1
]}

机构：

[1] Univ Helsinki, POB 24, Helsinki 00014, Finland

来源：

PHILOSOPHY OF SCIENCE | 2021年 / 88卷 / 05期

关键词：

RECEPTIVE FIELDS; MOTOR CONTROL; MODELS;

D O I：

10.1086/715513

中图分类号：

N09 [自然科学史]; B [哲学、宗教];

学科分类号：

01 ; 0101 ; 010108 ; 060207 ; 060305 ; 0712 ;

摘要：

According to radical enactivists, cognitive sciences should abandon the representational framework. Perceptuomotor cognition and action control are often provided as paradigmatic examples of nonrepresentational cognitive phenomena. In this article, we illustrate how motor and action control are studied in research that uses reinforcement learning algorithms. Crucially, this approach can be given a representational interpretation. Hence, reinforcement learning provides a way to explicate action-oriented views of cognitive systems in a representational way.

引用

页码：1045 / 1054

页数：10

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