國立虎尾科技大學 |

Multi-Agent Control in Sociotechnical Systems Coordinating Intelligent Individuals with Soft Regulation.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Multi-Agent Control in Sociotechnical Systems Coordinating Intelligent Individuals with Soft Regulation./
作者:	Luo, Yu.
面頁冊數:	1 online resource (175 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-07(E), Section: B.
Contained By:	Dissertation Abstracts International78-07B(E).
標題:	Chemical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781369559989

Multi-Agent Control in Sociotechnical Systems Coordinating Intelligent Individuals with Soft Regulation.
Luo, Yu.

Multi-Agent Control in Sociotechnical Systems Coordinating Intelligent Individuals with Soft Regulation. - 1 online resource (175 pages)

Source: Dissertation Abstracts International, Volume: 78-07(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

This item is not available from ProQuest Dissertations & Theses.

Process control is essential in chemical engineering and has diverse applications in automation, manufacturing, scheduling, etc. In this cross-disciplinary work, we shift the domain focus from the control of machines to the control of multiple intelligent agents. Our goal is to improve the optimization problem-solving process, such as optimal regulation of emerging technologies, in a multi-agent system. Achieving that improvement would have potential value both within and outside the chemical engineering community. This work also illustrates the possibility of applying process systems engineering techniques, especially process control, beyond chemical plants.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369559989Subjects--Topical Terms:

555952
Chemical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Multi-Agent Control in Sociotechnical Systems Coordinating Intelligent Individuals with Soft Regulation.
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500 $a Source: Dissertation Abstracts International, Volume: 78-07(E), Section: B.
500 $a Adviser: Venkat Venkatasubramanian.
502 $a Thesis (Ph.D.) $c Columbia University $d 2017.
504 $a Includes bibliographical references
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a Process control is essential in chemical engineering and has diverse applications in automation, manufacturing, scheduling, etc. In this cross-disciplinary work, we shift the domain focus from the control of machines to the control of multiple intelligent agents. Our goal is to improve the optimization problem-solving process, such as optimal regulation of emerging technologies, in a multi-agent system. Achieving that improvement would have potential value both within and outside the chemical engineering community. This work also illustrates the possibility of applying process systems engineering techniques, especially process control, beyond chemical plants.
520 $a It is very common to observe crowds of individuals solving similar problems with similar information in a largely independent manner. We argue here that the crowds can become more efficient and robust problem-solvers, by partially following the average opinion. This observation runs counter to the widely accepted claim that the wisdom of crowds deteriorates with social influence. The key difference is that individuals are self-interested and hence will reject feedbacks that do not improve their performance. We propose a multi-agent control-theoretic methodology --- soft regulation --- to model the collective dynamics and compute the degree of social influence, i.e., the level to which one accepts the population feedback, that optimizes the problem-solving performance.
520 $a Soft regulation is a modeling language for multi-agent sociotechnical systems. The state-space formulation captures the individual learning process (i.e., open loop dynamics) as well as the influence of the population feedback in a straightforward manner. It can model a diverse set of existing multi-agent dynamics. Through numerical analysis and linear algebra, we attempt to understand the role of feedback in multi-agent collective dynamics, thus achieving multi-agent control in sociotechnical systems.
520 $a Our analysis through mathematical proofs, simulations, and a human subject experiment suggests that intelligent individuals, solving the same problem (or similar problems), could do much better by adaptively adjusting their decisions towards the population average. We even discover that the crowd of human subjects could self-organize into a near-optimal setting. This discovery suggests a new coordination mechanism for enhancing individual decision-making. Potential applications include mobile health, urban planning, and policymaking.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Chemical engineering. $3 555952
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650 4 $a Applied mathematics. $3 1069907
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710 2 $a Columbia University. $b Chemical Engineering. $3 1181665
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