2026-09-19T08:36:54Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/101132 2023-07-11 col_2142_5131 col_2142_14787 com_2142_5130 com_2142_9630 com_2142_234

Baryshnikov, Yuliy Hovakimyan, Naira Liberzon, Daniel Belabbas, Mohamed Ali Chen, Cheng 2018-09-04T20:33:55Z 2018-09-04T20:33:55Z 2020-09-05T09:15:26Z 2018-03-28 2018-05 Distributed artificial intelligence (DAI) and multi-agent system (MAS) has recently gained increasing interest due to its vast applications in real-world problems. Inspired by the natural MAS, this thesis primarily focuses on the study of the collective intelligence and the joint behavior of MAS, which are typically generated by a group of intelligent agents applied with autonomous controls. In particular, the collective intelligence is described as geometric group patterns, stationary distribution and cooperative motions in this thesis. As the size of the group increases, it is essential to exploit simple and distributed controls to achieve the desired collective intelligence of the system with robustness and minimal cost. Therefore, this thesis proposes two bio-inspired applications of MAS to illustrate that simple controls can obtain stable and robust limiting collective behaviors. Besides, topological configuration space is introduced to describe the admissible collective behaviors and design the cooperative controls. In the first part of the thesis, cyclic pursuit as a periodic joint behavior of the MAS is studied. With prescribed deployments and controls of the agents, the limiting group geometric formation varies from regular polygons to an eight-shaped graph. The rotation number of the graph is a geometric invariant during the evolution. In the second application, the cyclic collective intelligence is generalized to a swarm concentration problem with desired gathering and drifting group behaviors. Randomized algorithms are used to localize the agents and generate stationary distributions of the swarm. In the last part of the thesis, topological configuration space is implemented to assist the design of hybrid controls for a multi-agent coverage problem. Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-05-01 The student, Cheng Chen, accepted the attached license on 2018-03-27 at 17:17. The student, Cheng Chen, submitted this Dissertation for approval on 2018-03-27 at 17:30. This Dissertation was approved for publication on 2018-03-28 at 16:52. DSpace SAF Submission Ingestion Package generated from Vireo submission #12092 on 2018-08-31 at 17:17:53 Made available in DSpace on 2018-09-04T20:33:55Z (GMT). No. of bitstreams: 4 CHEN-DISSERTATION-2018.pdf: 2034266 bytes, checksum: ff8a7873c9f8be76ac24ebac03fd0d5a (MD5) Chen Permission Letter 1.pdf: 125579 bytes, checksum: 81eb16e88f9c7f0834dbfb4fae24a30d (MD5) Chen Permission Letter 2.pdf: 125295 bytes, checksum: 7f52b75a0803d95fe74d4912962a86c5 (MD5) LICENSE.txt: 4207 bytes, checksum: be663db3471420038032172607b0a91e (MD5) Previous issue date: 2018-03-28 Embargo set by: Seth Robbins for item 107215 Lift date: 2020-09-04T20:34:13Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 107215 Lift date: 2020-09-04T20:37:00Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 107215 Lift date: 2020-09-04T20:42:08Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 107215 on 2020-09-05T09:15:26Z. application/pdf http://hdl.handle.net/2142/101132 en Copyright 2018 Cheng Chen Control Multi-agent System Cyclic Pursuit Swarm Covering Topological Configuration Space Control and collective intelligence of multi-agent system text text Mechanical Sci & Engineering Mechanical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.