Engineered system architectures leveraging collaboration among multiple actors across organizational boundaries are envisioned to be more flexible, robust, or efficient than independent alternatives but also carry significant downside risks from new interdependencies added between constituents. This paper transitions the concept of risk dominance from equilibrium selection in game theory to engineering design as a strategic measure of collective stability for system of systems. A proposed method characterizes system design as a bi-level problem with two or more asymmetric decision-makers. A measure of risk dominance assesses strategic dynamics with respect to the stability of joint or collaborative architectures relative to independent alternatives using a novel linearization technique to approximate linear incentives among actors. An illustrative example case for an asymmetric three-player design scenario shows how strategic risk dominance can identify and mitigate architectures with unstable risk-reward dynamics.
Alkim Avsar presented a paper on August 19, 2019 titled “The Effects of Locus of Control and Big Five Personality Traits on Collaborative Engineering Design Tasks with Negotiation ” at the 2019 ASME International Design Engineering Technical Conferences (IDETC) Design Theory and Methodology (DTM) Conference in Anaheim California.
Abstract: Collaborative systems design is a human-centered activity dependent on individual decision-making processes. Personality traits have been found to influence individual behaviors and tendencies to compete or cooperate. This paper investigates the effects of Big Five and Locus of Control personality traits on negotiated outcomes of a simplified collaborative engineering design task. Secondary data includes results from short-form personality inventories and outcomes of pair design tasks. The data includes ten sessions of four participants each, where each participant completes a sequence of 12 pair tasks involving design space exploration and negotiation. Regression analysis shows a statistically-significant relationship between Big Five and Locus of Control and total individual value accumulated across the 12 design tasks. Results show the Big Five, aggregating extraversion, agreeableness, conscientiousness, neuroticism, and intellect/imagination to a single factor, negatively affects individual value and internal Locus of Control positively affects individual value. Future work should consider a dedicated experiment to refine understanding of how personality traits influence collaborative systems design and propose interventions to improve collaborative design processes.
Abstract: Earth observing systems are undergoing an architectural transformation to perform novel scientific campaigns by dynamically composing assets from government and commercial partners. Correspondingly, campaign-level engineering methods and tools must accommodate greater degrees of decentralized control and independence. This paper reviews advances provided by semantic web technology and distributed simulation to highlight some of the challenges in modeling Earth observing systems of systems. A campaign simulation framework organizes the contextual, structural, and behavioral features necessary to model Earth observing systems from a system of systems perspective. Finally, a multi-actor value framework considers interactive negotiation of non-commensurate preferences by participating entities.
Two CoDe Lab members were recently recognized for outstanding efforts in the School of Systems and Enterprises.
Henry Lee (M.E. Systems Engineering ’18) was recognized with the best master’s thesis award for his work titled “Measuring the Strategic Risk of Collaboration for Satellite Programs, A Case Study on the National Polar-orbiting Satellite System.”
Jamey Laughland (M.E. student in Space Systems Engineering) was recognized for academic achievement in the systems engineering program.
A new open accessarticle co-authored with Prof. Martin Törngren of KTH Royal Institute of Technology appears in a special issue of Designs on Challenges and Directions Forward for Dealing with the Complexity of Future Smart Cyber-Physical Systems.
Abstract: Cyber-Physical Systems (CPS) integrate computation, networking and physical processes to produce products that are autonomous, intelligent, connected and collaborative. Resulting Cyber-Physical Systems of Systems (CPSoS) have unprecedented capabilities but also unprecedented corresponding technological complexity. This paper aims to improve understanding, awareness and methods to deal with the increasing complexity by calling for the establishment of new foundations, knowledge and methodologies. We describe causes and effects of complexity, both in general and specific to CPS, consider the evolution of complexity, and identify limitations of current methodologies and organizations for dealing with future CPS. The lack of a systematic treatment of uncertain complex environments and “composability”, i.e., to integrate components of a CPS without negative side effects, represent overarching limitations of existing methodologies. Dealing with future CPSoS requires: (i) increased awareness of complexity, its impact and best practices for how to deal with it, (ii) research to establish new knowledge, methods and tools for CPS engineering, and (iii) research into organizational approaches and processes to adopt new methodologies and permit efficient collaboration within and across large teams of humans supported by increasingly automated computer aided engineering systems.
Location: CCSE lab, Babbio, Stevens Institute of Technology.
Title: Allocative Mechanisms And Information Exchange In Task Processing And Interactive Networks
Abstract: This thesis investigates analysis techniques and mechanisms for exchanging and valuating resources and information in a task processing network of elements (TNE) and interactive social networks. For a federated TNE, a trusted auctioneer uses a mechanism to allocate resources to computational tasks and suggests prices for exchanging resources across a federation. An operational mechanism allocates processing, storage and communication resources to computational demands. This model finds an efficient solution to combinatorial routing with technical and financial constraints. Using mixed-integer linear programming (MILP) formulation, the operational model finds an optimal solution to processing tasks, allocating links, storing and delivering data to destinations. The auctioneer assumes a federation of self-centric and rational strategic participants/bidders/federates and simulation results show improvement in collective and expected values for federates. For mechanism design in a federated TNE, this research investigates an auctioneer equipped with auction-based algorithms to drive behavior of decentralized components towards higher collective-efficient metrics. This work formulates five auction-based algorithms for exchanging resources and combinatorial routing in a federated network: 1) linear program with binary search for prices, 2) first-price reverse-bid double auction, 3) non-linear searching for prices, 4) online algorithm with closed-form solution for prices, and 5) virtual pricing in a multi-source and multi-hop routing case. Metrics for numerical validation include normalized bids and prices, collective values, and pricing convergence rate of algorithms. Extensive simulation runs using hundreds of topologies with different configurations of elements and federates show better computational performance and higher economic efficiency for the online algorithm with a closed-form and variation-reducing solution for prices. Finally, this thesis investigates incentivizing mechanisms for information exchange in interactive social networks by clustering and modeling viral topics on social networks as a collective result of micro-level behavior of interactive components (participants). Analysis investigates the nature of influence and interactions on social networks. A data-driven approach observes endogenous and exogenous influences on emergence of linguistic topics and content on Twitter based on metrics such as popularity, burstiness, relevance score, consolidation, and hierarchal and temporal similarities. Conclusions outline future work to capture behavioral metrics of users on evolution of content and discourse in the interactive social network.
Abstract: The experiment studies the effect of technical and social sources of complexity on effort required to complete abstracted design tasks. Parameter design tasks define a set of input design parameters and functional requirements modeled with a linear coupling matrix. Selecting design variables to meet all functional requirements within error limits completes a task. Technical complexity arises from the number and degree of coupling between design parameters. Social complexity arises from the number of designers involved in a task. The experiment includes 10 sessions with between 19 and 24 rounds of randomly generated parameter design tasks each having between two and six design variables and one, two, or three designers. Designers completed individual tasks in parallel during rounds. This article contains raw and post-processed data from 374 completed tasks ranging in effort from a few seconds for simple tasks to more than 15 min for complex ones.
Two papers were presented this week at the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE) in Quebec City, Canada.
Toward a Model-based Experimental Approach to Assessing Collective Systems Design Processes
A. Valencia Romero and P.T. Grogan in Design Theory Methodology (DTM)
Abstract: This work presents a conceptual model of collective decision-making processes in engineering systems design to understand the tradeoffs, risks, and dynamics between autonomous but interacting design actors. The proposed approach combines value-driven design, game theory, and simulation experimentation to study how technical and social factors of a design decision-making process facilitate or inhibit collective action. The collective systems design model considers two levels of decision-making: 1) lower-level design value exploration; and 2) upper-level design strategy selection. At the first level, the actors concurrently explore two strategy-specific value spaces with coupled design decision variables. Each collective decision is mapped to an individual scalar measure of preference (design value) that each actor seeks to maximize. At the second level, each of the actor’s design values from the two lower-level design exploration tasks is assigned to one diagonal entry of a normal-form game, with off-diagonal elements calculated in function of the “sucker’s” and “temptation-to-defect” payoffs in a classical strategy game scenario. The model helps generate synthetic design problems with specific strategy dynamics between autonomous actors. Results from a preliminary multi-agent simulation study assess the validity of proposed design spaces and generate hypotheses for subsequent studies using human subjects.
Operational and Strategic Decisions in Engineering Design Games
P.T. Grogan and A.E. Bayrak in Design Automation Conference (DAC)
Abstract: Engineering design games model decision-making activities by incorporating human participants in an entertaining platform. This article distinguishes between design decisions at operational and strategic timescales as important features of engineering design games. Operational decisions consider static and short-term dynamic decisions to establish a player’s situation awareness and initial entertainment. Strategic decisions consider longer-term dynamic decisions subject to large uncertainties to retain player engagement. However, constraints on cognitive load limit the ability to simultaneously address both lower-level operational design decisions and higher-level strategic decisions such as collaboration or sustainability. Partial automation can be introduced to reduce cognitive load for operational decisions and focus additional effort on strategic decisions. To illustrate tradeoffs between operational and strategic decisions, this paper discusses example cases for two existing games: Orbital Federates and EcoRacer. Discussion highlights the role of automation and entertainment in engaging human participants in engineering design games and makes recommendations for design of future engineering design games.