Spatio-temporal patterns act as computational mechanisms governing emergent behavior in robotic swarms

Terry Jack, M.D.A., Khuman, S.A. and Owa, K. ORCID: 0000-0002-1393-705X, 2019. Spatio-temporal patterns act as computational mechanisms governing emergent behavior in robotic swarms. International Journal of Swarm Intelligence and Evolutionary Computation, 8 (1): 175.

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Abstract

Our goal is to control a robotic swarm without removing its swarm-like nature. In other words, we aim to intrinsically control a robotic swarm emergent behavior. Past attempts at governing robotic swarms or their self-coordinating emergent behavior, has proven ineffective, largely due to the swarm's inherent randomness (making it difficult to predict) and utter simplicity (they lack a leader, any kind of centralized control, long-range communication, global knowledge, complex internal models and only operate on a couple of basic, reactive rules). The main problem is that emergent phenomena itself is not fully understood, despite being at the forefront of current research. Research into 1D and 2D Cellular Automata has uncovered a hidden computational layer which bridges the micro-macro gap (i.e., how individual behaviors at the micro-level influence the global behaviors on the macro-level). We hypothesize that there also lie embedded computational mechanisms at the heart of a robotic swarm's emergent behavior. To test this theory, we proceeded to simulate robotic swarms (represented as both particles and dynamic networks) and then designed local rules to induce various types of intelligent, emergent behaviors (as well as designing genetic algorithms to evolve robotic swarms with emergent behaviors). Finally, we analysed these robotic swarms and successfully confirmed our hypothesis; analyzing their developments and interactions over time revealed various forms of embedded spatiotemporal patterns which store, propagate and parallel process information across the swarm according to some internal, collision-based logic (solving the mystery of how simple robots are able to self-coordinate and allow global behaviors to emerge across the swarm).

Item Type: Journal article
Publication Title: International Journal of Swarm Intelligence and Evolutionary Computation
Creators: Terry Jack, M.D.A., Khuman, S.A. and Owa, K.
Date: 25 February 2019
Volume: 8
Number: 1
Identifiers:
NumberType
10.4172/2090-4908.1000175DOI
1244592Other
Rights: Copyright: © 2019 Terry Jack MDA, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Divisions: Schools > School of Science and Technology
Depositing User: Linda Sullivan
Date Added: 28 Jan 2020 12:43
Last Modified: 28 Jan 2020 12:43
URI: http://irep.ntu.ac.uk/id/eprint/39101

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