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1. A normative approach for resilient multiagent systems

   https://doi.org/10.1007/s10458-023-09627-4  

   Mahala, Geeta; Kafalı, Özgür; Dam, Hoa; Ghose, Aditya; Singh, Munindar P (December 2023, Autonomous Agents and Multi-Agent Systems)

   We model a multiagent system (MAS) in socio-technical terms, combining a social layer consisting of norms with a technical layer consisting of actions that the agents execute. This approach emphasizes autonomy, and makes assumptions about both the social and technical layers explicit. Autonomy means that agents may violate norms. In our approach, agents are computational entities, with each representing a different stakeholder. We express stakeholder requirements of the form that a MAS is resilient in that it can recover (sufficiently) from a failure within a (sufficiently short) duration. We present ReNo, a framework that computes probabilistic and temporal guarantees on whether the underlying requirements are met or, if failed, recovered. ReNo supports the refinement of the specification of a socio-technical system through methodological guidelines to meet the stated requirements. An important contribution of ReNo is that it shows how the social and technical layers can be modeled jointly to enable the construction of resilient systems of autonomous agents. We demonstrate ReNo using a manufacturing scenario with competing public, industrial, and environmental requirements. 

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2. Pippi: Practical Protocol Instantiation

   Samuel H. Christie V, Amit K. (May 2022, AAMAS Conference proceedings)

   A protocol specifies interactions between roles, which together constitute a multiagent system (MAS). Enacting a protocol presupposes that agents are bound to the its roles. Existing protocol-based approaches, however, do not adequately treat the practical aspects of how roles bindings come about. Pippi addresses this problem of MAS instantiation. It proposes the notion of a metaprotocol, enacting which instantiates a MAS suitable for enacting a given protocol. Pippi demonstrates the subtleties involved in instantiating MAS arising from protocol composition, correlation, and decentralization. To address these subtleties and further support practical application patterns, we introduce an enhanced protocol language, with support for parameter types (including role and protocol typed parameters, for metaprotocols),interface flexibility, and binding constraints. We discuss the realization of our approach through an extended agent architecture,including the novel concept of a MAS adapter for contact management. We evaluate Pippi’s expressiveness by demonstrating common patterns for agent discovery. 

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3. Systems Engineering Initiative for Student Success (SEISS) Framework for Transforming Organizational Designs

   Pennathur, Arunkumar; Pennathur, Priyadarshini; Blosser, Emily; Bowman, Nicholas (June 2023, ASEE 2023 Annual Conference and Exposition)

   In this paper, we present the Systems Engineering Initiative for Student Success (SEISS) framework we are developing for enabling educational organizations to scan, evaluate and transform their operations to achieve their diversity, equity, and inclusion goals in student recruitment, retention, and graduation. The underlying structure and logic in our SEISS framework is that an organization such as a college of engineering is a sociotechnical system (STS) consisting of a social subsystem and a technical subsystem. The social subsystem consists of people, their roles and is a model of who talks to whom about what. The technical subsystem consists of all the activities, programs, policies, and operations that help the organization achieve its goals. In a sociotechnical system, the social and technical subsystems are interdependent in their functioning, and they must be jointly optimized from an organizational design perspective. Our SEISS framework which views a college or a similar organizational unit as a sociotechnical system lends the organizational designer a unique systems lens with which to view, analyze and design the operations and organize the capacities and resources in the college. The systems lens views an organizational unit, its sub-systems, components, and its corresponding capacities not in isolation, but as entities that interact with each other. With support from an NSF IUSE grant, we have been developing the SEISS framework and have piloted the framework in a predominantly white college of engineering to identify existing and potential technical and social system capacities for underrepresented minority (URM) students to succeed in the college. Preliminary results from our qualitative analyses of URM student interviews reveal the utility of the SEISS framework and the STS lens in unearthing the barriers and enablers for these students in the social and technical subsystems in the college. We also model the interactions between the social and technical subsystem elements in the SEISS framework, revealing latent opportunities for leveraging the connections between the social and technical subsystem capacities and resources. 

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4. A Framework of Digital Twins for Modeling Human-Subject Word Formation Experiments

   He, Hao; Liu, Xueying; Kuhlman, Chris J; Deng, Xinwei (December 2024, IEEE)

   Agent-based models (ABMs) are used to simulate human-subject experiments. A comprehensive understanding of these human systems often requires executing large numbers of simulations, but these requirements are constrained by computational and other resources. In this work, we build a framework of digital twins for modeling human-subject experiments. The framework has three modules: ABMs of player behaviors built from game data; extensions of these models to represent virtual assistants (agents that are exogenously manipulated to create controlled environments for human agents); and an uncertainty quantification module composed of functional ANOVA and a Gaussian process-based emulator. The emulator is built from the extended ABM; we focus on emulator validation. By incorporating experimental data and agent-based simulation data, our proposed framework enhances the virtual representation of the dynamics in human-subject word formation experiments, which we consider a digital twin. Networked anagram experiments are used as an exemplar to demonstrate the methods. 

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5. A Cost-Aware Multi-Agent System for Black-Box Design Space Exploration

   https://doi.org/10.1115/1.4065914  

   Chen, Siyu; Bayrak, Alparslan Emrah; Sha, Zhenghui (August 2024, Journal of Mechanical Design)

   Effective coordination of design teams must account for the influence of costs incurred while searching for the best design solutions. This article introduces a cost-aware multi-agent system (MAS), a theoretical model to (1) explain how individuals in a team should search, assuming that they are all rational utility-maximizing decision-makers and (2) study the impact of cost on the search performance of both individual agents and the system. First, we develop a new multi-agent Bayesian optimization framework accounting for information exchange among agents to support their decisions on where to sample in search. Second, we employ a reinforcement learning approach based on the multi-agent deep deterministic policy gradient for training MAS to identify where agents cannot sample due to design constraints. Third, we propose a new cost-aware stopping criterion for each agent to determine when costs outweigh potential gains in search as a criterion to stop. Our results indicate that cost has a more significant impact on MAS communication in complex design problems than in simple ones. For example, when searching in complex design spaces, some agents could initially have low-performance gains, thus stopping prematurely due to negative payoffs, even if those agents could perform better in the later stage of the search. Therefore, global-local communication becomes more critical in such situations for the entire system to converge. The proposed model can serve as a benchmark for empirical studies to quantitatively gauge how humans would rationally make design decisions in a team. 

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