Modular self-organization

TL;DR

This paper proposes a framework combining autonomous planning and data clustering to enable the automatic construction of modular architectures for autonomous agents.

Contribution

It introduces a novel integration of Markov Decision Processes with kernel-based clustering for self-organizing modular agent design.

Findings

Framework effectively combines planning and clustering

Enables autonomous modular architecture construction

Provides a theoretical basis for self-organization

Abstract

The aim of this paper is to provide a sound framework for addressing a difficult problem: the automatic construction of an autonomous agent's modular architecture. We combine results from two apparently uncorrelated domains: Autonomous planning through Markov Decision Processes and a General Data Clustering Approach using a kernel-like method. Our fundamental idea is that the former is a good framework for addressing autonomy whereas the latter allows to tackle self-organizing problems.