Sensorimotor communication for humans and robots: improving interactive skills by sending coordination signals

Haris Dindo, Francesco Donnarumma, Giovanni Pezzulo

Risultato della ricerca: Article

3 Citazioni (Scopus)

Abstract

During joint actions, humans continuously exchange coordination signals and use non-verbal, sensorimotor forms of communication. Here we discuss a specific example of sensorimotor communication – “signaling” – which consists in the intentional modification of one’s own action plan (e.g., a plan for reaching a glass of wine) to make it more predictable or discriminable from alternative action plans that are contextually plausible (e.g., a plan for reaching another glass on the same table). We first review the existing evidence on signaling in human-human interactions, discussing under which conditions humans use signaling. Successively, we distill these insights into a computational theory of signaling during on-line interactions. Central to our approach are the following ideas: (1) signaling endows pragmatic plans with communicative goals; (2) signaling can be understood within a cost-benefit scheme, balancing the costs for the signaling agent against its benefits for interaction success; (3) signaling may be part of an interactive strategy that optimizes success when joint goals are uncertain. Finally, we exemplify the benefits of signaling in a series of simulations and discuss how endowing robots with signaling abilities can increase the quality of HRIs by making their behavior more predictable and “legible” for humans
Lingua originaleEnglish
pagine (da-a)903-917
Numero di pagine15
RivistaIEEE Transactions on Cognitive and Developmental Systems
Volume10
Stato di pubblicazionePublished - 2018

Fingerprint

Robots
Communication
Glass
Wine
Costs

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

Cita questo

@article{f17033700f30426b8265310e2043f0ff,
title = "Sensorimotor communication for humans and robots: improving interactive skills by sending coordination signals",
abstract = "During joint actions, humans continuously exchange coordination signals and use non-verbal, sensorimotor forms of communication. Here we discuss a specific example of sensorimotor communication – “signaling” – which consists in the intentional modification of one’s own action plan (e.g., a plan for reaching a glass of wine) to make it more predictable or discriminable from alternative action plans that are contextually plausible (e.g., a plan for reaching another glass on the same table). We first review the existing evidence on signaling in human-human interactions, discussing under which conditions humans use signaling. Successively, we distill these insights into a computational theory of signaling during on-line interactions. Central to our approach are the following ideas: (1) signaling endows pragmatic plans with communicative goals; (2) signaling can be understood within a cost-benefit scheme, balancing the costs for the signaling agent against its benefits for interaction success; (3) signaling may be part of an interactive strategy that optimizes success when joint goals are uncertain. Finally, we exemplify the benefits of signaling in a series of simulations and discuss how endowing robots with signaling abilities can increase the quality of HRIs by making their behavior more predictable and “legible” for humans",
author = "Haris Dindo and Francesco Donnarumma and Giovanni Pezzulo",
year = "2018",
language = "English",
volume = "10",
pages = "903--917",
journal = "IEEE Transactions on Cognitive and Developmental Systems",
issn = "2379-8920",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Sensorimotor communication for humans and robots: improving interactive skills by sending coordination signals

AU - Dindo, Haris

AU - Donnarumma, Francesco

AU - Pezzulo, Giovanni

PY - 2018

Y1 - 2018

N2 - During joint actions, humans continuously exchange coordination signals and use non-verbal, sensorimotor forms of communication. Here we discuss a specific example of sensorimotor communication – “signaling” – which consists in the intentional modification of one’s own action plan (e.g., a plan for reaching a glass of wine) to make it more predictable or discriminable from alternative action plans that are contextually plausible (e.g., a plan for reaching another glass on the same table). We first review the existing evidence on signaling in human-human interactions, discussing under which conditions humans use signaling. Successively, we distill these insights into a computational theory of signaling during on-line interactions. Central to our approach are the following ideas: (1) signaling endows pragmatic plans with communicative goals; (2) signaling can be understood within a cost-benefit scheme, balancing the costs for the signaling agent against its benefits for interaction success; (3) signaling may be part of an interactive strategy that optimizes success when joint goals are uncertain. Finally, we exemplify the benefits of signaling in a series of simulations and discuss how endowing robots with signaling abilities can increase the quality of HRIs by making their behavior more predictable and “legible” for humans

AB - During joint actions, humans continuously exchange coordination signals and use non-verbal, sensorimotor forms of communication. Here we discuss a specific example of sensorimotor communication – “signaling” – which consists in the intentional modification of one’s own action plan (e.g., a plan for reaching a glass of wine) to make it more predictable or discriminable from alternative action plans that are contextually plausible (e.g., a plan for reaching another glass on the same table). We first review the existing evidence on signaling in human-human interactions, discussing under which conditions humans use signaling. Successively, we distill these insights into a computational theory of signaling during on-line interactions. Central to our approach are the following ideas: (1) signaling endows pragmatic plans with communicative goals; (2) signaling can be understood within a cost-benefit scheme, balancing the costs for the signaling agent against its benefits for interaction success; (3) signaling may be part of an interactive strategy that optimizes success when joint goals are uncertain. Finally, we exemplify the benefits of signaling in a series of simulations and discuss how endowing robots with signaling abilities can increase the quality of HRIs by making their behavior more predictable and “legible” for humans

UR - http://hdl.handle.net/10447/310047

M3 - Article

VL - 10

SP - 903

EP - 917

JO - IEEE Transactions on Cognitive and Developmental Systems

JF - IEEE Transactions on Cognitive and Developmental Systems

SN - 2379-8920

ER -