Virtual Software Corporations (VSCs) are a novel and important organisational form for large-scale software development. The increased complexity of this development environment requires the use of tools to support human actors in undertaking their tasks, which in turn require modelling solutions able to capture the VSC specific issues. One of the key aspects identified for software development in a VSC setting is the need to support co-ordination. One approach in the development of support for coordination in heterogeneous environments in respect to processes and support tools, such as VSCs, is the use of commitment management. The purpose of this thesis is to define a formalism suitable for capturing and managing commitments, as a means to support co-ordination. This is done by first analysing existing VSCs, and determining the requirements for co-ordination support. Consequently a formalism is defined to address the requirements. The formalism is based on a commitment modelling approach and deontic logic, a modal logic, which is used to manage the commitments. The defined formalism is the basis of a prototype support system, which is used for testing and evaluating. The evaluation has focused on identifying the level of support provided for the initial requirements. To this end three process examples have been used: the initial case study, the study of an independent VSC and the example of a desired process for software configuration management.The results indicate that the formalism, through the use of the prototype system, is able to represent and to manage commitments, as the most important issues in coordinating VSC software development. Thus it has a significant contribution as a modelling approach and it was shown to be applicable to realistic process scenarios.

The research described in this thesis is an attempt to utilize the Model Driven Architecture for semi-automatically developing a prototype Multi-Agent System to support the management of a real container terminal. Agent technology has been increasingly applied in Transport Logistics and seems to be a viable solution to support the container terminal management. Thus, from the user point of view, the focus of this research is to investigate the applicability of Multi-Agent Systems to assist the container terminal's decision makers in improving the container terminal productivity, which is often measured in terms of the productivity of cranes. A prototype Multi-Agent System has been developed to evaluate and compare a set of proposed vehicle dispatching strategies, which are a collection of rules that a vehicle (e.g. straddle carrier) uses to decide the priority of serving the working cranes. Employing an appropriate dispatching strategy may greatly improve the efficiency of vehicle allocation to the working cranes, so as to increase the utilization of cranes which directly enhance the container terminal productivity. In order to investigate the applicability of the Multi-Agent System for supporting the container terminal management, experiments have been conducted in a variety of real-world scenarios. The experiment results have revealed that Multi-Agent Systems are applicable to assist container terminal decision makers in evaluating operating strategies. On the other hand, from the developer point of view, the author investigates how to apply the Model Driven Architecture to agent technologies, providing a partially automated support for the derivation of Multi-Agent System implementation from the agent-oriented design, independently from the target implementation platforms. The Model Driven Architecture approach studied in this research is a model-driven software development process that explicitly separates models at three different levels of abstraction: platform independent models, platform specific models, and implementation models. In contrast to the conventional code-centric software development, the Model Driven Architecture based software development uses models as the primary engineering artifacts. The adopted development approach is to take a high-level abstraction model of a system and transform it into a set of platform specific models, each of which is in turn transformed into the corresponding implementation. Transformations between models are automatically carried out by a set of transformation tools. The experience of using the Model Driven Architecture for the development of the prototype Multi-Agent System has revealed the following benefits: (a) automated transformations between models increase software productivity; (b) separating the high-level specification of the system from the underlying implementation technology improves the portability of the system's high-level abstraction model; (c) strong separation of concerns, guaranteed consistency between models, and automatic generation of source code minimize future software maintenance effort.

The research described in this thesis is an attempt to utilize the Model Driven Architecture for semi-automatically developing a prototype Multi-Agent System to support the management of a real container terminal. Agent technology has been increasingly applied in Transport Logistics and seems to be a viable solution to support the container terminal management. Thus, from the user point of view, the focus of this research is to investigate the applicability of Multi-Agent Systems to assist the container terminal's decision makers in improving the container terminal productivity, which is often measured in terms of the productivity of cranes. A prototype Multi-Agent System has been developed to evaluate and compare a set of proposed vehicle dispatching strategies, which are a collection of rules that a vehicle (e.g. straddle carrier) uses to decide the priority of serving the working cranes. Employing an appropriate dispatching strategy may greatly improve the efficiency of vehicle allocation to the working cranes, so as to increase the utilization of cranes which directly enhance the container terminal productivity. In order to investigate the applicability of the Multi-Agent System for supporting the container terminal management, experiments have been conducted in a variety of real-world scenarios. The experiment results have revealed that Multi-Agent Systems are applicable to assist container terminal decision makers in evaluating operating strategies. On the other hand, from the developer point of view, the author investigates how to apply the Model Driven Architecture to agent technologies, providing a partially automated support for the derivation of Multi-Agent System implementation from the agent-oriented design, independently from the target implementation platforms. The Model Driven Architecture approach studied in this research is a model-driven software development process that explicitly separates models at three different levels of abstraction: platform independent models, platform specific models, and implementation models. In contrast to the conventional code-centric software development, the Model Driven Architecture based software development uses models as the primary engineering artifacts. The adopted development approach is to take a high-level abstraction model of a system and transform it into a set of platform specific models, each of which is in turn transformed into the corresponding implementation. Transformations between models are automatically carried out by a set of transformation tools. The experience of using the Model Driven Architecture for the development of the prototype Multi-Agent System has revealed the following benefits: (a) automated transformations between models increase software productivity; (b) separating the high-level specification of the system from the underlying implementation technology improves the portability of the system's high-level abstraction model; (c) strong separation of concerns, guaranteed consistency between models, and automatic generation of source code minimize future software maintenance effort.

Sharing common goals and acting cooperatively are critical issues in multiagent teamwork. Traditionally, agents cooperate with each other by inferring others' actions implicitly or explicitly, based on established norms for behavior or on knowledge about the preferences or interests of others. This kind of cooperation either requires that agents share a large amount of knowledge about the teamwork, which is unrealistic in a distributed team, or requires high-frequency message exchange, which weakens teamwork efficiency, especially for a team that may involve human members. In this research, we designed and developed a new approach called Proactive Communication, which helps to produce realistic behavior and interactions for multiagent teamwork. We emphasize that multi-agent teamwork is governed by the same principles that underlie human cooperation. Psychological studies of human teamwork have shown that members of an effective team often anticipate the needs of other members and choose to assist them proactively. Human team members are also naturally capable of observing the environment and others so they can establish certain parameters for performing actions without communicating with others. Proactive Communication endows agents with observabilities and enables agents use them to track others’ mental states. Additionally, Proactive Communication uses statistical analysis of the information production and need of team members and uses these data to capture the complex, interdependent decision processes between information needer and provider. Since not all these data are known, we use their expected values with respect to a dynamic estimation of distributions. The approach was evaluated by running several sets of experiments on a Multi- Agent Wumpus World application. The results showed that endowing agents with observability decreased communication load as well as enhanced team performance. The results also showed that with the support of dynamic distributions, estimation, and decision-theoretic modeling, teamwork efficiency were improved.

abstract: This work describes an approach for distance computation between agents in a multi-agent swarm. Unlike other approaches, this work relies solely on signal Angleof- Arrival (AoA) data and local trajectory data. Each agent in the swarm is able to discretely determine distance and bearing to every other neighbor agent in the swarm. From this information, I propose a lightweight method for sensor coverage of an unknown area based on the work of Sameera Poduri. I also show that this technique performs well with limited calibration distances. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2020

Um subconjunto importante da pesquisa em sistemas multiagentes (SMA) baseiase no estudo das organizações. A organização define a estrutura do SMA e as regras que os agentes devem seguir, a fim de aumentar a eficiência do sistema. No entanto, dado um domínio, a escolha da organização que melhor resolve o problema ainda é uma questão sem resposta. Assim, abordagens empíricas para a avaliação de organizações são importantes, pois fornecem indícios valiosos sobre os custos e benefícios de diferentes configurações organizacionais, ajudando desenvolvedores e projetistas na definição da organização a ser adotada. Neste contexto, este trabalho, compara e avalia o impacto da mudança de parâmetros organizacionais no desempenho de um SMA, cujo objetivo é competir no cenário Agents on Mars proposto no Multi-Agent Programming Contest (MAPC). / An important subset of multi-agent systems (MAS) are based on the study of organizations. The organization defines the MAS structure and the rules which the agents must follow, increasing the MAS efficiency. Given an application domain, however, the choice of a particular organization that better solves the problem is still an open problem. Therefore, empirical approaches to the evaluation of organizations are important since they provide valuable evidences about the costs and benefits of different organizational settings, helping developers and designers to define the organization to be adopted. In this context, this work compares and evaluates the impact of organizational changes in the performance of a MAS, whose goal is to evolve in the \"Agents on Mars\" scenario proposed in the Multi-Agent Programming Contest (MAPC).

Um subconjunto importante da pesquisa em sistemas multiagentes (SMA) baseiase no estudo das organizações. A organização define a estrutura do SMA e as regras que os agentes devem seguir, a fim de aumentar a eficiência do sistema. No entanto, dado um domínio, a escolha da organização que melhor resolve o problema ainda é uma questão sem resposta. Assim, abordagens empíricas para a avaliação de organizações são importantes, pois fornecem indícios valiosos sobre os custos e benefícios de diferentes configurações organizacionais, ajudando desenvolvedores e projetistas na definição da organização a ser adotada. Neste contexto, este trabalho, compara e avalia o impacto da mudança de parâmetros organizacionais no desempenho de um SMA, cujo objetivo é competir no cenário Agents on Mars proposto no Multi-Agent Programming Contest (MAPC). / An important subset of multi-agent systems (MAS) are based on the study of organizations. The organization defines the MAS structure and the rules which the agents must follow, increasing the MAS efficiency. Given an application domain, however, the choice of a particular organization that better solves the problem is still an open problem. Therefore, empirical approaches to the evaluation of organizations are important since they provide valuable evidences about the costs and benefits of different organizational settings, helping developers and designers to define the organization to be adopted. In this context, this work compares and evaluates the impact of organizational changes in the performance of a MAS, whose goal is to evolve in the \"Agents on Mars\" scenario proposed in the Multi-Agent Programming Contest (MAPC).

A multi-agent system consists of a number of agents, which may include software agents, robots, or even humans, in some application environment. Multi-robot systems are increasingly being employed to complete jobs and missions in various fields including search and rescue, space and underwater exploration, support in healthcare facilities, surveillance and target tracking, product manufacturing, pick-up and delivery, and logistics. Multi-agent task allocation is a complex problem compounded by various constraints such as deadlines, agent capabilities, and communication delays. In high-stake real-time environments, such as rescue missions, it is difficult to predict in advance what the requirements of the mission will be, what resources will be available, and how to optimally employ such resources. Yet, a fast response and speedy execution are critical to the outcome. This thesis proposes distributed optimisation techniques to tackle the following questions: how to maximise the number of assigned tasks in time restricted environments with limited resources; how to reach consensus on an execution plan across many agents, within a reasonable time-frame; and how to maintain robustness and optimality when factors change, e.g. the number of agents changes. Three novel approaches are proposed to address each of these questions. A novel algorithm is proposed to reassign tasks and free resources that allow the completion of more tasks. The introduction of a rank-based system for conflict resolution is shown to reduce the time for the agents to reach consensus while maintaining equal number of allocations. Finally, this thesis proposes an adaptive data-driven algorithm to learn optimal strategies from experience in different scenarios, and to enable individual agents to adapt their strategy during execution. A simulated rescue scenario is used to demonstrate the performance of the proposed methods compared with existing baseline methods.

Current research in multi-agent systems (MAS) has advanced to the development of open MAS, which are characterized by the heterogeneity of agents, free exit/entry and decentralized control. Conflicts of interest among agents are inevitable, and hence automated negotiation to resolve them is one of the promising solutions. This thesis studies three modifications on alternating-offer bargaining protocols for automated negotiation in open MAS. The long-term goal of this research is to design negotiation protocols which can be easily used by intelligent agents in accommodating their need in resolving their conflicts. In particular, we propose three modifications: allowing non-monotonic offers during the bargaining (non-monotonic-offers bargaining protocol), allowing strategic delay (delay-based bargaining protocol), and allowing strategic ignorance to augment argumentation when the bargaining comprises argumentation (ignorance-based argumentation-based negotiation protocol). <p>Utility theory and decision-theoretic approaches are used in the theoretical analysis part, with an aim to prove the benefit of these three modifications in negotiation among myopic agents under uncertainty. Empirical studies by means of computer simulation are conducted in analyzing the cost and benefit of these modifications. Social agents, who use common human bargaining strategies, are the subjects of the simulation. <p>In general, we assume that agents are bounded rational with various degrees of belief and trust toward their opponents. In particular in the study of the non-monotonic-offers bargaining protocol, we assume that our agents have diminishing surplus. We further assume that our agents have increasing surplus in the study of delay-based bargaining protocol. And in the study of ignorance-based argumentation-based negotiation protocol, we assume that agents may have different knowledge and use different ontologies and reasoning engines. <p>Through theoretical analysis under various settings, we show the benefit of allowing these modifications in terms of agents expected surplus. And through simulation, we show the benefit of allowing these modifications in terms of social welfare (total surplus). Several implementation issues are then discussed, and their potential solutions in terms of some additional policies are proposed. Finally, we also suggest some future work which can potentially improve the reliability of these modifications.

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