A Framework for Optimizing Co-adaptation in Body-Machine Interfaces.

ABSTRACT: The operation of a human-machine interface is increasingly often referred to as a two-learners problem, where both the human and the interface independently adapt their behavior based on shared information to improve joint performance over a specific task. Drawing inspiration from the field of body-machine interfaces, we take a different perspective and propose a framework for studying co-adaptation in scenarios where the evolution of the interface is dependent on the users' behavior and that do not require task goals to be explicitly defined. Our mathematical description of co-adaptation is built upon the assumption that the interface and the user agents co-adapt toward maximizing the interaction efficiency rather than optimizing task performance. This work describes a mathematical framew

SUBMITTER: De Santis D 

PROVIDER: S-EPMC8097093 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature