Timescales of Change in Connectionist and Dynamical Systems Approaches to Learning and Development

Karl M. Newell; Yeou Teh Liu; Gottfried Mayer-Kress

doi:10.1093/acprof:oso/9780195300598.003.0006

Timescales of Change in Connectionist and Dynamical Systems Approaches to Learning and Development

Karl M. Newell^*, Yeou Teh Liu, Gottfried Mayer-Kress

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter

5 Citations (Scopus)

Abstract

This chapter examines the origins of the construct of timescales as expressed in Waddington's (1957) metaphor for development of the epigenetic landscape, and its subsequent use as a metaphor for change in learning/development in theoretical frameworks, both connectionist and dynamical systems. It presents an epigenetic landscape model for motor learning and development, which is constructed as a lowdimensional approximation of a high-dimensional (or infinitely dimensional) complex dynamical system that possesses a score, error, or fitness function. The chapter concludes by illustrating briefly three case studies of the timescales of change in the epigenetic landscape framework to motor learning and development.

Original language	English
Title of host publication	Toward a Unified Theory of Development Connectionism and Dynamic System Theory Re-Consider
Publisher	Oxford University Press
ISBN (Electronic)	9780199867165
ISBN (Print)	9780195300598
DOIs	https://doi.org/10.1093/acprof:oso/9780195300598.003.0006
Publication status	Published - 2009 Sept 1
Externally published	Yes

Keywords

Change
Epigenetic landscape model
Motor development
Motor learning

ASJC Scopus subject areas

General Psychology

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10.1093/acprof:oso/9780195300598.003.0006

Cite this

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AB - This chapter examines the origins of the construct of timescales as expressed in Waddington's (1957) metaphor for development of the epigenetic landscape, and its subsequent use as a metaphor for change in learning/development in theoretical frameworks, both connectionist and dynamical systems. It presents an epigenetic landscape model for motor learning and development, which is constructed as a lowdimensional approximation of a high-dimensional (or infinitely dimensional) complex dynamical system that possesses a score, error, or fitness function. The chapter concludes by illustrating briefly three case studies of the timescales of change in the epigenetic landscape framework to motor learning and development.

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KW - Motor learning

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Timescales of Change in Connectionist and Dynamical Systems Approaches to Learning and Development

Abstract

Keywords

ASJC Scopus subject areas

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