Engineering complex systems with multigroup agents

Doctor of PhilosophyComputing and Information SciencesScott A. DeLoachAs sensor prices drop and computing devices continue to become more compact and powerful, computing capabilities are being embedded throughout our physical environment. Connecting these devices in cyber-physical systems (CPS) enables applications with significant societal impact and economic benefit. However, engineering CPS poses modeling, architecture, and engineering challenges and, to fully realize the desired benefits, many outstanding challenges must be addressed. For the cyber parts of CPS, two decades of work in the design of autonomous agents and multiagent systems (MAS) offers design principles for distributed intelligent systems and formalizations for agent-oriented software engineering (AOSE). MAS foundations offer a natural fit for enabling distributed interacting devices. In some cases, complex control structures such as holarchies can be advantageous. These can motivate complex organizational strategies when implementing such systems with a MAS, and some designs may require agents to act in multiple groups simultaneously. Such agents must be able to manage their multiple associations and assignments in a consistent and unambiguous way. This thesis shows how designing agents as systems of intelligent subagents offers a reusable and practical approach to designing complex systems. It presents a set of flexible, reusable components developed for OBAA++, an organization-based architecture for single-group MAS, and shows how these components were used to develop the Adaptive Architecture for Systems of Intelligent Systems (AASIS) to enable multigroup agents suitable for complex, multigroup MAS. This work illustrates the reusability and flexibility of the approach by using AASIS to simulate a CPS for an intelligent power distribution system (IPDS) operating two multigroup MAS concurrently: one providing continuous voltage control and a second conducting discrete power auctions near sources of distributed generation

Bipartite containment of heterogeneous multi-agent systems under denial-of-service attacks: a historical information-based control scheme

A distributed control scheme based on historical information is designed to solve the problem of stable control of multi-agent systems under denial of service (DoS) attacks in this article. It achieves the control objective of bipartite output containment control, that is, the output states of the followers smoothly enter the target area. The control scheme updates the states of followers through historical information in the control protocol when agents are subjected to DoS attacks. A distributed state observer with a storage module is designed to efficiently estimate the state of followers and store the observed information as history information. The historical information of control protocol calls is not necessarily the real state information in the existence of DoS attacks. Consequently, a closed-loop feedback state compensator is designed. Then, the state compensator is converted from the time domain to the frequency domain for stability analysis using the Nyquist criterion. It is obtained that an upper bound on the amount of historical information can achieve the bipartite output trajectories containment of the controlled system. The output trajectories of the followers converge into two dynamic convex hulls, one of which is surrounded by multiple leaders, and the other is a convex hull with opposite signs of the leaders. Finally, a numerical simulation is used to verify the proposed control scheme, and the operability of the scheme is further demonstrated in a physical experiment

Resilient Output Consensus Control of Heterogeneous Multi-agent Systems against Byzantine Attacks: A Twin Layer Approach

This paper studies the problem of cooperative control of heterogeneous multi-agent systems (MASs) against Byzantine attacks. The agent affected by Byzantine attacks sends different wrong values to all neighbors while applying wrong input signals for itself, which is aggressive and difficult to be defended. Inspired by the concept of Digital Twin, a new hierarchical protocol equipped with a virtual twin layer (TL) is proposed, which decouples the above problems into the defense scheme against Byzantine edge attacks on the TL and the defense scheme against Byzantine node attacks on the cyber-physical layer (CPL). On the TL, we propose a resilient topology reconfiguration strategy by adding a minimum number of key edges to improve network resilience. It is strictly proved that the control strategy is sufficient to achieve asymptotic consensus in finite time with the topology on the TL satisfying strongly $(2f+1)$-robustness. On the CPL, decentralized chattering-free controllers are proposed to guarantee the resilient output consensus for the heterogeneous MASs against Byzantine node attacks. Moreover, the obtained controller shows exponential convergence. The effectiveness and practicality of the theoretical results are verified by numerical examples

Studying the Executive Perception of Investment in Intelligent Systems and the Effect on Firm Performance

This research was conducted to examine the relationship between investment in intelligent systems resources and capabilities (based on artificial intelligence and machine learning algorithms) and the effect on company performance. Despite existing research on the benefits of adopting intelligent systems, companies have been slow to adopt as there is lack of research on intelligent systems use cases that will increase firm performance. This research study used resource-based view (RBV) and dynamic capabilities (DCF) theory to investigate firms’ investment in intelligent systems resources that build intelligent systems capabilities and the association to organization performance dimensions, revenue and profits. To answer this question, an online survey was administered and received responses from 165 participants from companies in Canada and USA. The study findings provide empirical evidence that intelligent systems infrastructure resources and intelligent systems IT human resources increase firm performance, but intelligent systems business resources constructs selected for the study do not contribute to firm performance

Designing Adaptive Instruction for Teams: a Meta-Analysis

The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or educational experience tailored by artificially-intelligent, computer-based tutors with the goal of optimizing learner outcomes (e.g., knowledge and skill acquisition, performance, enhanced retention, accelerated learning, or transfer of skills from instructional environments to work environments). The core contribution of this research was the identification of behavioral markers associated with the antecedents of team performance and learning thus enabling the development and refinement of teamwork models in ITS architectures. Teamwork focuses on the coordination, cooperation, and communication among individuals to achieve a shared goal. For ITSs to optimally tailor team instruction, tutors must have key insights about both the team and the learners on that team. To aid the modeling of teams, we examined the literature to evaluate the relationship of teamwork behaviors (e.g., communication, cooperation, coordination, cognition, leadership/coaching, and conflict) with team outcomes (learning, performance, satisfaction, and viability) as part of a large-scale meta-analysis of the ITS, team training, and team performance literature. While ITSs have been used infrequently to instruct teams, the goal of this meta-analysis make team tutoring more ubiquitous by: identifying significant relationships between team behaviors and effective performance and learning outcomes; developing instructional guidelines for team tutoring based on these relationships; and applying these team tutoring guidelines to the Generalized Intelligent Framework for Tutoring (GIFT), an open source architecture for authoring, delivering, managing, and evaluating adaptive instructional tools and methods. In doing this, we have designed a domain-independent framework for the adaptive instruction of teams

Power of Near-Peers: Conceptualizing and Testing a Near-Peer Mentoring Model in Raising Youths\u27 Self-Efficacy in Computer Programming

Self-efficacy is seen as a barrier for youth, females in particular, to enter computer science (CS). In this study, I presented a near-peer mentoring model that focused on changing the mentee’s self-efficacy in CS. The present study had three objectives: (a) to design a near-peer mentoring model (i.e., a conceptual model) around the sources of information that influence self-efficacy, (b) to develop a mentor training model based on the conceptual model, and (c) to test the effectiveness of the training model in increasing mentees’ self-efficacy in the context of a summer App programming camp. The present study adopted a mixed-methods approach following a concurrent, embedded design to answer research questions. Data were collected from pre-post surveys and camper interviews. Comparison of quantitative and qualitative findings indicated that the near-peer mentoring model has a potential in increasing youth’s self-efficacy regardless of their gender. It was also found that encouragement was important for fostering self-efficacy and while they did not directly influence self-efficacy, modeling and instructive feedback enhanced campers’ learning experience, which, in turn, would boost self-efficacy. The present study also provided examples of how to train mentors to do modeling and provide instructive and encouraging feedback, which may be helpful for programs that use mentors to recruit youth to CS

Blockchain for supply chain traceability and anticounterfeiting: the oracles’ enabling role

Blockchain and physical oracles in the Collectible Industry. Supply chain fairness and bargaining power in agriculture supply chain: the blockchain effect. Unlocking the Blockchain Potentials through Oracles: Empirical Evidences on Supply Chain Challenges and Performance