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5 - Simulation theory of understanding others: a robotics perspective

Published online by Cambridge University Press:  10 December 2009

Yiannis Demiris
Affiliation:
Department of Electrical and Electronic Engineering, Imperial College, London, UK
Matthew Johnson
Affiliation:
Department of Electrical and Electronic Engineering, Imperial College, London, UK
Chrystopher L. Nehaniv
Affiliation:
University of Hertfordshire
Kerstin Dautenhahn
Affiliation:
University of Hertfordshire
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Summary

Introduction

Simulation theory

According to the simulation theory, ‘human beings are able to use the resources of their own minds to simulate the psychological etiology of the behaviour of others’, typically by making decisions within a ‘pretend context’ (Gordon, 1999). During observation of another agent's behaviour, the execution apparatus of the observer is taken ‘off-line’ and is used as a manipulable model of the observed behaviour.

From a roboticist's point of view, the fundamental characteristics of the simulation theory are:

  • Utilization of the same computational systems for a dual purpose; both behaviour generation as well as recognition.

  • Taking systems off-line (suspending their normal input/output) which necessitates a redirection and suppression of input (feeding ‘pretend states’ following a perspective taking process, suppressing the current ones that are coming from the visual sensors while this is performed) and output from/to the system to achieve this dual use.

Simulation theory is often set as a rival to the ‘theory-theory’, where a separate theoretical reasoning system is used; the observer perceives and reasons about the observed behaviour not by simulating it, but by utilizing a set of causal laws about behaviours.

It is important to note that in the experiments we describe here, ‘understanding’ the demonstrated behaviour equates to inferring its goal in terms of sensorimotor states, and does not imply inference of the emotional, motivational and intentional components of mental states.

Type
Chapter
Information
Imitation and Social Learning in Robots, Humans and Animals
Behavioural, Social and Communicative Dimensions
, pp. 89 - 102
Publisher: Cambridge University Press
Print publication year: 2007

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