Controlling the Sense of Agency in Dyadic Robot Interaction: An Active Inference Approach

by   Nadine Wirkuttis, et al.

This study investigated how social interaction among robotic agents changes dynamically depending on individual sense of agency. In a set of simulation studies, we examine dyadic imitative interactions of robots using a variational recurrent neural network model. The model is based on the free energy principle such that interacting robots find themselves in a loop, attempting to predict and infer each other's actions using active inference. We examined how regulating the complexity term to minimize free energy during training determines the dynamic characteristics of networks and affects dyadic imitative interactions. Our simulation results show that through softer regulation of the complexity term, a robot with stronger agency develops and dominates its counterpart developed with weaker agency through tighter regulation. When two robots are trained with equally soft regulation, both generate individual intended behavior patterns, ignoring each other. We argue that primary intersubjectivity does develop in dyadic robotic interactions.



page 4


Control of Pneumatic Artificial Muscles with SNN-based Cerebellar-like Model

Soft robotics technologies have gained growing interest in recent years,...

Cyber Human Interaction

Cyber human interaction is a broad term encompassing the range of intera...

Predicting Responses to a Robot's Future Motion using Generative Recurrent Neural Networks

Robotic navigation through crowds or herds requires the ability to both ...

Why robots should be technical: Correcting mental models through technical architecture concepts

Research in social robotics is commonly focused on designing robots that...

Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks

We are approaching a future where social robots will progressively becom...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.