System-of-Systems Engineering - Liophant Simulation

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Agent-Based Behavioral Modeling• Agent Based Models are appropriate when [Bonabeau2002]:– Individual behavior is nonlinear and can be characterized bydiscrete decisions, thresholds, if-then rules, or nonlinearcoupling– Describing discontinuity in individual behavior is difficult withdifferential equations. For example, if a logistics officer ordersparts in batches, he may have a threshold for making partsrequests (rather than continuously demanding replacements forparts used)– History matters. Path-dependence, lagging responses, non-Markovian behavior, or temporal correlations including learningand adaptation are applicable to the system.– Averages are not good enough. Under certain conditions, smallfluctuations in a complex system can be amplified, so that thesystem is stable for incremental changes but unstable to largeperturbationsDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu34
System Dynamics Modeling• System Dynamics (SD) is amacro-level top-downapproach to modelingphenomena at high levels ofabstraction and aggregation• SD models portray thestructure ofinterrelationships betweenvariables with flows andstocks– Stocks are the variables inthe system– Flows represent change• Methods for rapid modelconstruction and validationare neededWealthof TCCMoneyin terrorcentersMoneygiven outto TMCExcitementHumanagentTerrortargetsTCmoneyTCCmoneyTerrorCentersABM:humaninteractionswith TCs andtargetsSystemdynamics:TerroristfundingSystem Dynamics Handles Complexity with a Top-Down View of the WorldDeveloping Methods and Techniques for System of Systems EngineeringDr. Dimitri Mavris, dimitri.mavris@ae.gatech.edu35
Page 1 and 2: Developing Methods and Techniques f
Page 3 and 4: The Aerospace Systems Design Labora
Page 5 and 6: Motivation- Emphasis on “Early-Ph
Page 7 and 8: What is a system?“A set of functi
Page 9 and 10: System of Systems• “A set or ar
Page 11 and 12: What is SoSE?• System of Systems
Page 13 and 14: The Evolution of New Ideas“All tr
Page 15 and 16: What is needed for this New Paradig
Page 17 and 18: An Architecture-based Approach to S
Page 19 and 20: The System Alternative Space• The
Page 21 and 22: The Architecture-based Technology E
Page 23 and 24: Extension to Systems-of-Systems Ana
Page 25 and 26: Fundamental Properties of a Complex
Page 27 and 28: Enablers for Complex SoS• Design
Page 29 and 30: Design of Experiments• Design of
Page 31 and 32: Design of Computer Simulation• Co
Page 33: Agent-Based Behavioral Modeling•
Page 37 and 38: Discrete Event Simulations• Discr
Page 41 and 42: Surrogate ModelsWhy do we use surro
Page 43 and 44: Challenges to Surrogate Modeling fo
Page 45 and 46: Fitting Modal ResponsesDeveloping M
Page 51 and 52: Pareto Optimal Solutions in Many Di
Page 53 and 54: Interactive Electronic Design Revie
Page 55 and 56: Collaboration and Integration in So
Page 57 and 58: Concluding Remarks• System of Sys
Page 59 and 60: Selecting a DesignDeveloping Method
Page 61 and 62: A New Paradigm Shift: Simulation Ba
Page 63 and 64: Which are simple? Which arecomplica
Page 65 and 66: What is a Markov Chain• Markov Ch
Page 67 and 68: Markov Chains• The transition pro

System-of-Systems Engineering - Liophant Simulation

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