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Swarm Intelligence in the Multi-Agent Environment A SWARM INTELLIGENCE IN THE MULTI-AGENT ENVIRONMENT A Master’s Thesis Presented to Department of Computer and Information Sciences SUNY Polytechnic Institute Utica, New York In Partial Fulfilment of the Requirements for the Master of Science Degree By Sravani Bollam December 2016 © Sravani Bollam 2016 ACKNOWLEDGEMENTS The completion of this thesis could not have been possible without the participation and assistance of my Professor Dr. Saumendra Sengupta. His contributions are genuinely appreciated and acknowledged. I would particularly like to thank my parents, Naveen Kumar and Madhavi Bollam who stood by me and gave me immense support by understanding my dreams. And I would also like to thank my siblings and friends for inspiring me and by sharing their support either morally or physically. ii ABSTRACT This thesis is focused on the use of naturally occurring concept of “swarm intelligence” to multi- agent systems, namely the relatively new system-theoretic framework known as Swarm Intelligence Systems (SIS). In this work, outlined is the general framework of an interacting agents behaving as a swarm group on a mission to deliver a service such as transporting a set of goods from a given starting point to a destination. As an example, one could think of a team of drones, for instance, providing a delivery service in a milieu where normal transportation mode may be prohibitively expensive. The entire logistic, in detail as a commercial project, is too involved for our thesis focus; instead, some of the structural interaction issues with a group are outlined and discussed here to articulate the behavior of multi-agent based swarm as a group necessary to function as a distributed entity somewhat different from the standard swarm models found in literature. iii Table of Contents 1. Introduction .......................................................................................................... 1 1.1 Overview ...................................................................................................................... 1 1.2 About ............................................................................................................................ 5 1.3 Why .............................................................................................................................. 7 1.4 Previous Work .............................................................................................................. 7 1.5 My take on this ............................................................................................................. 8 1.6 Organization of the Report ........................................................................................... 9 2. Literature Review ..............................................................................................10 2.1 Survey ......................................................................................................................... 10 3. Multi-Agent Systems – Swarm Robotics ..........................................................13 3.1 Introduction ................................................................................................................ 13 3.2 Natural Swarm Intelligent Systems ............................................................................ 14 3.3 Artificial Swarms ........................................................................................................ 17 3.4 Main set of rules – Standard assumptions .................................................................. 19 3.5 Travelling Salesman Problem ..................................................................................... 19 3.6 Unmanned Aerial Vehicle Applications ..................................................................... 20 3.7 General Applications .................................................................................................. 23 3.8 Problem Definition ..................................................................................................... 25 3.9 Algorithm.................................................................................................................... 26 3.10 Scalability ................................................................................................................... 27 3.11 Proposed Solution ....................................................................................................... 28 4. Extension ...........................................................................................................29 4.1 Overview .................................................................................................................... 29 4.2 Extend Problem .......................................................................................................... 30 4.3 Assumptions for extension ......................................................................................... 30 4.4 Solution for extended Problem ................................................................................... 31 4.5 System protection issue - Security .............................................................................. 38 iv 4.6 Experimental analysis ................................................................................................. 45 4.7 Results of the experiment ........................................................................................... 48 4.8 Graph .......................................................................................................................... 48 4.9 Conclusion .................................................................................................................. 49 v Table of Figures 1.1 (a): No interaction 1.1 (b): With Interactions .......................................................................................................... 2 1.1 (c): Too Large a swarm 1.1 (d): After split. Two cluster swarms .................................................................................. 3 1.1 (e) Evaluations in a split swarm .......................................................................................... 4 3.1 The Design patterns of Bees. ............................................................................................ 15 3.2 The waggle dance relative to the Sun indicating food location ........................................ 16 3.3 Sensefly’s ebee Drone Maps A Swiss Alpine Valley ....................................................... 21 3.4 MIT Senseable City Lab ................................................................................................... 21 3.5 Scaneagle coast gaurd ....................................................................................................... 22 3.6 Amazon Prime air drone ................................................................................................... 23 3.7 Navy Swarm boats ............................................................................................................ 24 3.8 Drone as a disinfectant ...................................................................................................... 24 4.1 Agent interacting with Leader and Neighbour .................................................................. 34 4.2 Agent path in case of Obstacles ........................................................................................ 36 4.3 Agents hierarchy ............................................................................................................... 36 4.4 Fragmentation in case of obstacles ................................................................................... 37 4.5 Communication configurations ......................................................................................... 41 4.6 Pictorial illustration of the task ......................................................................................... 47 4.7 Weights Vs. Threshold graph ........................................................................................... 49 vi << This Page intentionally left blank >> vii Chapter 1 1. Introduction 1.1 Overview Multi-robot systems [2] are an important tool for instances where an early response is vital or to progress to the places that are unreachable or very dangerous for people. Urban search and rescue, monitoring, planetary exploration, surveillance, cleaning, maintenance, among others are possible applications. High level of collaboration and self-sufficiency is required to complete the tasks successfully. Robots need to act as a team rather than acting as an entity [2]. As the individuals consume more time and often the solution provided by a single robot will often not be a more optimized solution. And when it comes to the scalability of larger tasks, single robot system is not a good option. In Multi-robot systems we can inculcate intelligence to solve a problem using local interactions by forming a swarm. It would be a more optimized and efficient method where algorithm’s scalability will play a crucial role. One way of acknowledging its structure is to realize that this specific design addressed in this thesis could be considered in the category of cooperative solution domain where each participant agent cooperates with the entire group to solve a specific problem entrusted via its mission. 1 Consider, for instance, a convoy of trucks to deliver goods from point A to point B. If the trucks do not cooperate with each other, we might be thinking of delivering goods in classical modes
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