System of Systems Modeling and Analysis
Learning Objective:Recognize problems that have system-of-systems traits; Understand the structure and behavior of such problems; Translate problem to addressable form; Formulate tailored analysis methodologies for these problems; Emphasis: modern network science and agent-based modeling; Synthesize solution candidates by understanding decision criteria; Articulate both problem and analysis in written and verbal formats.
Description:The goal for this course is to enable students to characterize, abstract, model, simulate, and analyze a special kind of system termed a system-of-systems (SoS). The course will cover a select few topics in detail, but also expose students to interesting areas of further study and highlight the importance of SoS in society. The course presents recent developments in frameworks for formulating system-of-systems problems, lexicon for their articulation, and analysis methodology for their study. Through individual and team projects, students gain experience in formulating problems and applying theory and techniques. Applications for team projects will include transportation, space exploration, energy, defense, and infrastructure, though others are possible in consultation with instructor. Spring 2018 Syllabus
Topics Covered:Topics (subject to modification):Course Introduction: "What is System-of-Systems (SoS) anyway..."; Literature Review on SoS and System-of-Systems Engineering; Characterizing & Delineating SoS problems; A Lexicon and Abstraction for describing SoS problems; Lineage and Related Domains - Representation; Lineage and Related Domains - Design/Decide; Lineage and Related Domains - Develop (Systems Engineering); Complexity/Complex Systems; Artificial Intelligence; Fundamentals of Evolutionary Modeling; Multi-agent Simulations (MAS), agent-based modeling; Some mathematical formulations (probability and statistics); Network Science; Evaluation: solution spaces, evaluation architectures, ratios, scenarios; Evaluation/Optimization: multi-object, Pareto, robustness...; Verification/Validation/Accreditation.
Prerequisites:Open to any interested graduate students from any school and major (undergraduate students with senior standing need instructor's permission).
Applied / Theory:50 / 50
Web Content:Syllabus, grades, lecture notes, homework assignments, solutions, chat room and message board.
Projects:Working in teams of no more than 3 people, the team project allows students to demonstrate knowledge of key concepts through application, culminating in a final report and presentation. Students will self-select into teams according to their interest in project topics provided by instructor (or self-generated, in consultation with instructor). Teams must successfully apply the 3-phase approach to SoS modeling presented in class.
Exams:1 mid-term exam; no final exam
Textbooks:Official textbook information is now listed in the Schedule of Classes. NOTE: Textbook information is subject to be changed at any time at the discretion of the faculty member. If you have questions or concerns please contact the academic department.
Tentative: None required. Many papers will be assigned as required reading and Lecture Notes provided Suggestion: Modeling Complex Systems, Nino Boccara, 2004, Springer Series Graduate Texts in Contemporary Physics, ISBN 0-387-40462-7