title: Generation of diversity in a reaction-diffusion-based controller.
abstract: A controller of biological or artificial organism (e.g., in bio-inspired cellular robots) consists of a number of processes that drive its dynamics. For a system of processes to perform as a successful controller, different properties can be mentioned. One of the desirable properties of such a system is the capability of generating sufficiently diverse patterns of outputs and behaviors. A system with such a capability is potentially adaptable to perform complicated tasks with proper parameterizations and may successfully reach the solution space of behaviors from the point of view of search and evolutionary algorithms. This article aims to take an early step toward exploring this capability at the levels of individuals and populations by introducing measures of diversity generation and by evaluating the influence of different types of processes on diversity generation. A reaction-diffusion-based controller called the artificial homeostatic hormone system (AHHS) is studied as a system consisting of different processes with various domains of functioning (e.g., internal or external to the control unit). Various combinations of these processes are investigated in terms of diversity generation at levels of both individuals and populations, and the effects of the processes are discussed representing different influences for the processes. A case study of evolving a multimodular AHHS controller with all the various process combinations is also investigated, representing the relevance of the diversity generation measures and practical scenarios.
authors.affiliation: Karl-Franzens University Graz.
authors.forename: Payam
authors.initials: P
authors.lastname: Zahadat
authors.forename: Thomas
authors.initials: T
authors.lastname: Schmickl
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D004058:Diffusion; D006706:Homeostasis; D019369:Life
keywords: Diversity; bio-inspired control; evolutionary computation; modular robotics; reaction-diffusion-based control