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

Donnarumma, F., Dindo, H., Pezzulo, G. (2018). Sensorimotor communication for humans and robots: improving interactive skills by sending coordination signals. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 10(4), 903-917 [10.1109/TCDS.2017.2756107].

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

Dindo, Haris;
2018-01-01

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
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Donnarumma, F., Dindo, H., Pezzulo, G. (2018). Sensorimotor communication for humans and robots: improving interactive skills by sending coordination signals. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 10(4), 903-917 [10.1109/TCDS.2017.2756107].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/310047
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