University of Hertfordshire

By the same authors

Intrinsically Motivated Autonomy in Human-Robot Interaction: Human Perception of Predictive Information in Robots

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems - 20th Annual Conference, TAROS 2019, Proceedings
EditorsKaspar Althoefer, Jelizaveta Konstantinova, Ketao Zhang
PublisherSpringer Verlag
Pages325-337
Number of pages13
ISBN (Print)9783030238063
DOIs
Publication statusPublished - 28 Jun 2019
Event20th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2019 - London, United Kingdom
Duration: 3 Jul 20195 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11649 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2019
CountryUnited Kingdom
CityLondon
Period3/07/195/07/19

Abstract

In this paper we present a fully autonomous and intrinsically motivated robot usable for HRI experiments. We argue that an intrinsically motivated approach based on the Predictive Information formalism, like the one presented here, could provide us with a pathway towards autonomous robot behaviour generation, that is capable of producing behaviour interesting enough for sustaining the interaction with humans and without the need for a human operator in the loop. We present a possible reactive baseline behaviour for comparison for future research. Participants perceive the baseline and the adaptive, intrinsically motivated behaviour differently. In our exploratory study we see evidence that participants perceive an intrinsically motivated robot as less intelligent than the reactive baseline behaviour. We argue that is mostly due to the high adaptation rate chosen and the design of the environment. However, we also see that the adaptive robot is perceived as more warm, a factor which carries more weight in interpersonal interaction than competence.

Notes

© Springer Nature Switzerland AG 2019

ID: 17414642