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

## TL;DR

This paper introduces an autonomous, intrinsically motivated robot using Predictive Information to generate engaging behaviors in human-robot interaction, highlighting differences in human perception of robot intelligence and warmth.

## Contribution

It presents a novel intrinsically motivated approach based on Predictive Information for autonomous robot behavior generation in HRI, with a comparative baseline and perceptual insights.

## Key findings

- Participants perceived the intrinsically motivated robot as less intelligent than the baseline.
- The adaptive robot was perceived as more warm, influencing interpersonal perception.
- High adaptation rate and environment design affected perceived intelligence.

## 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.