University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science

Este trabalho explora uma solução para tornar mais eficiente a recuperação de sinais estratégicos antecipativos na Internet, na chamada fase de rastreamento ou de captação de informação estratégica antecipativa, segundo diferentes autores, que descrevem ciclos da Inteligência Competitiva. Durante o texto a seguir serão descritos os conceitos de Inteligência Competitiva e de agentes inteligentes de software, considerada a solução ideal para suportar a recuperação de informação neste mundo imenso que é a Internet. Um protótipo será arquitetado para verificar a possibilidade de agentes serem uma boa representação e solução para o rastreamento de informação, com o objetivo de suportar o monitoramento estratégico do ambiente de uma organização. Estas informações, necessariamente, devem ser qualificadas, confiáveis e condizentes com um tema, atores e fontes predeterminados. A forma de obtenção das informações no ambiente Web pode ser feita diretamente e de forma discreta (no tempo) ou contínua, sem que seja acionada uma questão para busca direta, mas em resposta a um evento com características de interesse definidas. / This work explores a solution to making more efficient the recovery of antecipative strategical signals in the Internet, in the so-called tracking phase or antecipative strategical information captation phase, according to different authors describing cycles of Competitive Intelligence. In the text that follows, the concepts of Competitive Intelligence and intelligent agents of software will be described, considering the ideal solution to support the recovery of information in this immense world that is the Internet. A prototype will be set to verify the possibility of agents being good representation and a solution for the tracking of information, with the objective of supporting the strategical monitoring of an organization?s environment. These pieces of information must necessarily be qualified, trustworthy and related to predetermined subject, actors and sources. The attainment of information in the Web environment can be direct and of discrete form (within time constraints) or continuum, without inputting a question for direct search, but in reply to an event with definite characteristics of interest.

A contabilidade é ciência destinada ao tratamento da informação de eventos econômicos que ocorrem dentro das organizações. Diversas técnicas de registro e tratamento de dados foram desenvolvidas ao longo do tempo para gerar informações relevantes nas tomadas de decisões. Nesse sentido, a contabilidade tem sua origem no método das partidas dobradas (lançamentos de débito e crédito), conhecido por modelo DCA (Debit-Credit Accounting), que considera as variações monetárias do patrimônio. Com o advento da tecnologia da informação surgem, efetivamente, os sistemas de informação contábeis, que buscam dar maior autonomia aos processos de desenvolvimento dos bancos de dados. Na década de 80 surge o modelo REA (economic Resources, economic Events e economic Agents), que se baseia no registro da informação contábil com base na associação entre os recursos-econômicos, eventos-econômicos e agentes-econômicos, possibilitando ganhos na capacidade de geração de informação ao usuário. O objetivo deste trabalho é demonstrar estes sistemas de informação contábeis e sua evolução, bem como, propor uma modelagem de dados orientada a objetos com a utilização de agentes inteligentes, baseado em inteligência artificial, para o desenvolvimento e análise da informação. Além disso, o modelo proposto é analisado segundo as qualidades necessárias à informação contábil para os usuários da informação contábil. / Accounting is a science focused on economic event information treatment inside entities. Several register techniques and data treatment were developed over the years to generate relevant information for decision making. In this sense, accounting has its origin on the double entry method (debits and credits) known as the DCA model (Debit-Credit Accounting), which considers monetary variations. With development of information technologies, accounting information systems are born, giving bigger processes more autonomy and evolving data banks as well as the Entity-Relation model. In the 1980\'s, the REA model (economic Resources, economic Events and economic Agents) is created, which focuses on accounting information records based on the association of economic resources, economic events and economic agents, improving the capacity of generating information for the user. The objective of this work is to demonstrate these accounting information systems, their evolution and propose an object-oriented modeling with intelligent agents use, based on artificial intelligence, for information development and analysis. The proposed model is also analyzed according to accounting information quality necessary to accounting information users.

本論文包含四個部分。每一部分我們演示一個在共同演化網絡中的個體為本(agent-based)模型。第二章是不滿適應雪堆博奕(DASG)的廣泛化。第三章是自省適應(self-questioning adaptive)雪堆博奕。第四章是共同演化選民模型的廣泛化。第五章是有三個互相克制的角色的適應性石頭-布-剪刀(ARPS)模型。在這些模型中，適應行為導致共同演化過程發生。我們以電算模擬及理論方法研究這些模型。我們的目標是建立一個可應用於不同共同演化網絡的一般分析框架。 / 在第二章及第四章，我們將Gräser等人的DASG及Vazquez等人的共同演化選民模型從一個控制參數推廣到二個獨立的控制參數。在他們的工作中，根據網絡的結構定義了一些相，而且發展了平均場理論。而在廣泛化的情況下，在已伸延的相空間上，我們也定義了一些相及發展了一些廣泛化的平均場理論。在廣泛化DASG中，我們以考慮在相邊界附近的最終生存形態(last surviving patterns)以解釋相邊界的電算模擬結果。 / 在第三章，我們提出及研究一個以誘惑驅動的雪堆博奕。該更新機制被稱為自省機制(self-questioning mechanism)。我們給出模擬及理論結果，也討論了該些結果的物理意義。 / 在第五章，我們推廣我們的研究至有三個策略的遊戲。我們提出及研究了一個ARPS模型，其中每個個體採用三個互相克制的策略的其中之一。每個個體以概率 p來重連不理想的連結或以概率 (1 - p)改變自身的策略以適應其周遭環境。我們研究了網絡於不同的 p值在穩定態的行為及定義 了一些相。我們研究兩個選取重連對象的方法，分別對應於隨機選取及刻意選取重連對象，也解釋了得出的結果。我們在有關穩定勝利、平手及失敗概率的研究中及哪種個體可以有更高的勝利概率的研究中得出了有趣的結果。我們也研究了結果如何取決於初始條件。 / 在不同的模型中，理論方程均建立於相似的想法上。理論結果得出模擬結果的主要特性，包括出現了不同的相。該分析方法被證明了在本論文中對不同的模型也有效，而該方法也可被應用於很多其他共同演化網絡上。 / This thesis consists of four parts. In each part, we present results of an agent-based model of co-evolving network. Chapter 2 deals with a generalization of the Dissatisfied Adaptive Snowdrift Game (DASG) and Chapter 3 covers the self-questioning adaptive snowdrift game. Chapter 4 discusses a generalization of a co-evolving voter model. Chapter 5 gives the results on a cyclic three-character Adaptive Rock-Paper-Scissor (ARPS) game. The adaptive actions give rise to co-evolving processes in these models. These models are studied both numerically and analytically. An objective here is to establish a general analytic framework that is applicable to different models of co-evolving networks. / In Chapters 2 and 4, we generalize two existing models -the DASG of Gräser et al. and the co-evolving voter model of Vazquez et al. -from a single control parameter to two independent parameters. Different phases were identified according to the network structure and mean-field theories were developed in the previous work. With the expanded phase space in our generalized models, we identified different phases and provided a generalized mean-field approach. The phase boundaries in the generalized DASG can be explained by considering the last surviving patterns in the vicinity of the transition between two phases. / In Chapter 3, we propose and study a co-evolving snowdrift game in which the adaptive actions are driven by the desire to enhance winning. The updating scheme is called the self-questioning mechanism. We present simulation and theoretical results, and provide physical meaning to the results. / In Chapter 5, we extend our study to three-strategy games. An ARPS model in which each agent uses one of three strategies that dominate each other cyclically is proposed and studied. Each agent adapts his local environment by rewiring an un-favourable link with a probability p or switching his strategy with a probability 1-p. As p varies, the behaviour of the network in the steady state is studied and dierent phases are identified. Two dierent schemes corresponding to selecting the rewiring target randomly and intentionally are studied and the results are explained. Interesting results are also found in the probabilities of winning, losing and drawing in the steady state; and the type of agents that have a higher winning probability. The dependence on the initial distribution of the three strategies among the agents is also studied. / The analytic equations presented for each model in the thesis are established on similar ideas. The analytic results capture the main features in the simulation results, including the emergence of dierent phases. The analytic approach, proven to be useful through different models in this thesis, can be applied to a wide class of other co-evolving network models. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Choi, Chi Wun / 個體為本共同演化網絡的研究 / 蔡至桓. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 114-116). / Abstracts also in Chinese. / Choi, Chi Wun / Ge ti wei ben gong tong yan hua wang luo de yan jiu / Cai Zhihuan. / Abstract --- p.i / 摘要 --- p.iii / Acknowledgements --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Review --- p.5 / Chapter 1.2.1 --- Network and basic graph properties --- p.5 / Chapter 1.2.2 --- Two-person games --- p.6 / Chapter 2 --- Generalization of Dissatisfied-Adaptive Snowdrift Game (DASG) --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- Dissatisfied-Adaptive model --- p.12 / Chapter 2.3 --- Previous work --- p.14 / Chapter 2.4 --- Generalized Dissatisfied-Adaptive model --- p.16 / Chapter 2.5 --- Simulation results --- p.17 / Chapter 2.6 --- Theoretical analysis --- p.19 / Chapter 2.6.1 --- Mean-Field approach --- p.19 / Chapter 2.6.2 --- Theoretical results --- p.22 / Chapter 2.7 --- Last surviving patterns --- p.25 / Chapter 2.7.1 --- Observing the last surviving patterns --- p.25 / Chapter 2.7.2 --- Applying the theory using extracted information from simulations --- p.26 / Chapter 2.7.3 --- Further development of the theory --- p.28 / Chapter 2.7.4 --- Results of the theory --- p.30 / Chapter 2.8 --- Dependence on initial conditions and mean degree --- p.32 / Chapter 2.9 --- Conclusion --- p.34 / Chapter 3 --- Self-questioning Adaptive SG --- p.36 / Chapter 3.1 --- Introduction --- p.36 / Chapter 3.2 --- Self-questioning adaptive SG with control parameter r --- p.39 / Chapter 3.2.1 --- Model --- p.39 / Chapter 3.2.2 --- Results --- p.40 / Chapter 3.3 --- Self-questioning adaptive SG with control parameters r and h --- p.42 / Chapter 3.3.1 --- Model --- p.42 / Chapter 3.3.2 --- Results --- p.43 / Chapter 3.4 --- Conclusion --- p.45 / Chapter 4 --- Generalization of co-evolving voter model --- p.46 / Chapter 4.1 --- Introduction --- p.46 / Chapter 4.2 --- Co-evolving voter model --- p.49 / Chapter 4.3 --- Previous work --- p.50 / Chapter 4.4 --- Simulation results --- p.52 / Chapter 4.4.1 --- Results of macroscopic quantities --- p.52 / Chapter 4.4.2 --- Results of trajectories by simulations --- p.54 / Chapter 4.4.3 --- The largest component --- p.55 / Chapter 4.4.4 --- Short Summary --- p.56 / Chapter 4.5 --- Theoretical analysis --- p.57 / Chapter 4.5.1 --- Mean-Field approach --- p.57 / Chapter 4.5.2 --- Theoretical results --- p.59 / Chapter 4.6 --- Dependence on initial conditions and mean degree --- p.60 / Chapter 4.6.1 --- Results for different mean degrees --- p.60 / Chapter 4.6.2 --- Results for different initial conditions --- p.61 / Chapter 4.7 --- Conclusion --- p.63 / Chapter 5 --- Adaptive Rock-Paper-Scissors games --- p.64 / Chapter 5.1 --- Introduction --- p.64 / Chapter 5.2 --- Adaptive Rock-Paper-Scissors Model --- p.67 / Chapter 5.3 --- Simulation results --- p.70 / Chapter 5.4 --- Theoretical analysis --- p.73 / Chapter 5.4.1 --- Simplifications by threefold-symmetry --- p.73 / Chapter 5.4.2 --- Changes in local quantities --- p.74 / Chapter 5.4.3 --- Mean-Field approach --- p.75 / Chapter 5.4.4 --- Theoretical results --- p.80 / Chapter 5.5 --- Dependence on mean degree --- p.82 / Chapter 5.6 --- Oriented rewiring method --- p.83 / Chapter 5.7 --- Probabilities of winning, drawing and losing --- p.85 / Chapter 5.7.1 --- Average probabilities of winning, drawing and losing in the steady state --- p.85 / Chapter 5.7.2 --- Degree distribution and the distributions of the probabilities --- p.86 / Chapter 5.7.3 --- Brief explanation --- p.88 / Chapter 5.7.4 --- Results for a larger μ --- p.89 / Chapter 5.7.5 --- Short summary --- p.90 / Chapter 5.8 --- Results for general initial conditions --- p.92 / Chapter 5.8.1 --- Coupled dynamical equations --- p.92 / Chapter 5.8.2 --- Trajectories of the macroscopic quantities --- p.94 / Chapter 5.8.3 --- Phases and theoretical ternary phase diagrams --- p.96 / Chapter 5.9 --- Conclusion --- p.98 / Chapter 6 --- Summary --- p.100 / Chapter A --- Coupled dynamical equations for Self-questioning adaptive SG --- p.104 / Chapter B --- Theoretical results for Self-questioning adaptive SG with control parameters r and h --- p.106 / Chapter C --- Derivations of Mean-Field equations in ARPS model --- p.108 / Chapter D --- Derivations of Mean-Field equations for the oriented rewiring method in ARPS model --- p.111 / Bibliography --- p.114

by Zhao Lei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 78-85). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgments --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background --- p.5 / Chapter 2.1 --- Agents --- p.5 / Chapter 2.1.1 --- Deliberative Agents --- p.7 / Chapter 2.1.2 --- Reactive Agents --- p.8 / Chapter 2.1.3 --- Interacting Agents --- p.9 / Chapter 2.1.4 --- Hybrid Architectures --- p.10 / Chapter 2.2 --- Real-time Artificial Intelligence --- p.10 / Chapter 2.3 --- Real-Time Agents --- p.12 / Chapter 2.3.1 --- The Subsumption Architecture --- p.13 / Chapter 2.3.2 --- The InterRAP Architecture --- p.15 / Chapter 2.3.3 --- The 3T Architecture --- p.16 / Chapter 2.4 --- On-line Scheduling in Real-Time Agents --- p.18 / Chapter 3 --- A Real-Time Agent Architecture --- p.20 / Chapter 3.1 --- Human Cognition Model --- p.20 / Chapter 3.1.1 --- Perception --- p.22 / Chapter 3.1.2 --- Cognition --- p.22 / Chapter 3.1.3 --- Action --- p.23 / Chapter 3.2 --- Real-Time Message Passing Primitives and Process Structuring --- p.24 / Chapter 3.2.1 --- Message Passing as IPC --- p.25 / Chapter 3.2.2 --- Administrator and Worker Processes --- p.28 / Chapter 3.3 --- Agent Architecture --- p.29 / Chapter 3.3.1 --- Sensor Workers and the Sensor Administrator --- p.30 / Chapter 3.3.2 --- The Cognition Workers --- p.32 / Chapter 3.3.3 --- "The Task Administrator, the Scheduler Worker and Ex- ecutor Workers" --- p.32 / Chapter 3.4 --- An Agent-Based Real-time Arcade Game --- p.34 / Chapter 4 --- A Multiple Method Approach to Task Scheduling --- p.37 / Chapter 4.1 --- Task Scheduling Mechanism --- p.37 / Chapter 4.1.1 --- Task and Action --- p.38 / Chapter 4.1.2 --- Task Administrator --- p.40 / Chapter 4.1.3 --- Task Scheduler --- p.43 / Chapter 4.2 --- A Task Scheduling Model --- p.44 / Chapter 4.3 --- Combination Rules and Special Cases --- p.46 / Chapter 4.4 --- Scheduling Algorithms --- p.49 / Chapter 5 --- Task Scheduling Model: Analysis and Experiments --- p.53 / Chapter 5.1 --- Goodness Measure --- p.53 / Chapter 5.2 --- Theoretical Analysis --- p.54 / Chapter 5.3 --- Implementation --- p.59 / Chapter 5.3.1 --- Task Generator Implementation --- p.59 / Chapter 5.3.2 --- Executor Workers Implementation --- p.61 / Chapter 5.4 --- Experimental Results --- p.62 / Chapter 5.4.1 --- Hybrid Mechanism and Individual Algorithms --- p.63 / Chapter 5.4.2 --- Effect of Average Execution Time --- p.65 / Chapter 5.4.3 --- Effect of the Greedy Algorithm --- p.65 / Chapter 5.4.4 --- Effect of the Advanced Algorithm --- p.67 / Chapter 5.4.5 --- Effect of Actions and Relations Among Them --- p.68 / Chapter 5.4.6 --- Effect of Deadline --- p.71 / Chapter 6 --- Conclusions --- p.73 / Chapter 6.1 --- Summary of Contributions --- p.73 / Chapter 6.2 --- Future Work --- p.75

Lee Ting-on. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 116-121). / Abstracts in English and Chinese. / Acknowledgments --- p.i / Abstract --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Roadmap to the Thesis --- p.5 / Chapter 2 --- Software Agents and Agent Frameworks --- p.7 / Chapter 2.1 --- Software Agent --- p.7 / Chapter 2.1.1 --- Advantages of Agent --- p.10 / Chapter 2.1.2 --- Roles of Agent --- p.11 / Chapter 2.2 --- Agent Frameworks --- p.13 / Chapter 2.3 --- Communication Services and Concepts --- p.15 / Chapter 2.3.1 --- Message Channel --- p.15 / Chapter 2.3.2 --- Remote Procedure Call --- p.16 / Chapter 2.3.3 --- Event Channel --- p.17 / Chapter 2.4 --- Component --- p.18 / Chapter 3 --- Related Work --- p.20 / Chapter 3.1 --- Collaboration Behaviors --- p.20 / Chapter 3.2 --- Direct Coordination --- p.22 / Chapter 3.3 --- Meeting-oriented Coordination --- p.23 / Chapter 3.4 --- Blackboard-based Coordination --- p.24 / Chapter 3.5 --- Linda-like Coordination --- p.25 / Chapter 3.6 --- Reactive Tuple Spaces --- p.26 / Chapter 4 --- Background and Foundations --- p.27 / Chapter 4.1 --- Choice of Technologies --- p.27 / Chapter 4.2 --- Jini Technology --- p.28 / Chapter 4.2.1 --- The Lookup Service --- p.29 / Chapter 4.2.2 --- Proxy --- p.31 / Chapter 4.3 --- JavaSpaces --- p.32 / Chapter 4.4 --- Grasshopper Architecture --- p.33 / Chapter 5 --- The CoDAC Framework --- p.36 / Chapter 5.1 --- Requirements for Enabling Collaboration --- p.37 / Chapter 5.1.1 --- Consistent Group Membership --- p.37 / Chapter 5.1.2 --- Atomic Commitment --- p.39 / Chapter 5.1.3 --- Uniform Reliable Multicast --- p.40 / Chapter 5.1.4 --- Fault Tolerance --- p.40 / Chapter 5.2 --- System Components --- p.41 / Chapter 5.2.1 --- Distributed Agent Adapter --- p.42 / Chapter 5.2.2 --- CollaborationCore --- p.44 / Chapter 5.3 --- System Infrastructure --- p.45 / Chapter 5.3.1 --- Agent --- p.45 / Chapter 5.3.2 --- Distributed Agent Manager --- p.46 / Chapter 5.3.3 --- Collaboration Manager --- p.46 / Chapter 5.3.4 --- Kernel --- p.46 / Chapter 5.4 --- Collaboration --- p.47 / Chapter 5.5.1 --- Global Collaboration --- p.48 / Chapter 5.5.2 --- Local Collaboration --- p.48 / Chapter 6 --- Collaboration Life Cycle --- p.50 / Chapter 6.1 --- Initialization --- p.50 / Chapter 6.2 --- Resouces Gathering --- p.53 / Chapter 6.3 --- Results Delivery --- p.54 / Chapter 7 --- Protocol Suite --- p.55 / Chapter 7.1 --- The Group Membership Protocol --- p.56 / Chapter 7.1.1 --- Join Protocol --- p.56 / Chapter 7.1.2 --- Leave Protocol --- p.57 / Chapter 7.1.3 --- Recovery Protocol --- p.59 / Chapter 7.1.4 --- Proof --- p.61 / Chapter 7.2 --- Atomic Commitment Protocol --- p.62 / Chapter 7.3 --- Uniform Reliable Multicast --- p.63 / Chapter Chapter 8 --- Implementation --- p.66 / Chapter 8.1 --- Interfaces and Classes --- p.66 / Chapter 8.1.1 --- The CoDACAdapterInterface --- p.66 / Chapter 8.1.2 --- The CoDACEventListener --- p.69 / Chapter 8.1.3 --- The DAAdapter --- p.71 / Chapter 8.1.4 --- The DAManager --- p.75 / Chapter 8.1.5 --- The CoDACInternalEventListener --- p.77 / Chapter 8.1.6 --- The CollaborationManager --- p.77 / Chapter 8.1.7 --- The CollaborationCore --- p.78 / Chapter 8.2 --- Messaging Mechanism --- p.79 / Chapter 8.3 --- Nested Transaction --- p.84 / Chapter 8.4 --- Fault Detection --- p.85 / Chapter 8.5 --- Atomic Commitment Protocol --- p.88 / Chapter 8.5.1 --- Message Flow --- p.89 / Chapter 8.5.2 --- Timeout Actions --- p.91 / Chapter Chapter 9 --- Example --- p.93 / Chapter 9.1 --- System Model --- p.93 / Chapter 9.2 --- Auction Lifecycle --- p.94 / Chapter 9.2.1 --- Initialization --- p.94 / Chapter 9.2.2 --- Resource Gathering --- p.98 / Chapter 9.2.3 --- Results Delivery --- p.100 / Chapter Chapter 10 --- Discussions --- p.104 / Chapter 10.1 --- Compatibility --- p.104 / Chapter 10.2 --- Hierarchical Group Infrastructure --- p.106 / Chapter 10.3 --- Flexibility --- p.107 / Chapter 10.4 --- Atomicity --- p.108 / Chapter 10.5 --- Fault Tolerance --- p.109 / Chapter Chapter 11 --- Conclusion and Future Work --- p.111 / Chapter 11.1 --- Conclusion --- p.111 / Chapter 11.2 --- Future Work --- p.112 / Chapter 11.2.1 --- Electronic Commerce --- p.112 / Chapter 11.2.2 --- Workflow Management --- p.114 / Bibliography --- p.116 / Publication List --- p.121

In recent decades, millions of articles, books and journals have been written and thousandsseminars and conferences have been held to present increasing importance of supply chainmanagement both in practice and theory. Undoubtedly, nowadays, success is not tied-upjust in processes of a focal company but in processes of all its value chain and network. Inorder to survive in highly competitive markets, it sounds essential that all processes andentities of the supply and demand network be analyzed and value-adding ones be separatedfrom those which are not.One of the origins of non-value adding processes is non-value adding complexity. So, asystematic study and analysis of supply chain complexity and rendering remedies forsimplicity are essential.In this thesis, at first, some definitions as well as causes of supply chain complexity basedon its complication and complexity are mentioned. In the next step, embodiments of somethemes of complexity science in discipline of supply chains are explained. Later, a recipefor studying complexity is offered. Ingredients of this recipe are identification,classification, measurement, modeling, and simplification. Finally, implementation ofintelligent agents as assured tools for simplification of supply chains complexity isdescribed. / Uppsatsnivå: D

In infinitely repeated games, we also give definitions to risk attitude and reputation. As art infinitely repeated game is a repetition of a constituent strategic game, we transform each single round of an infinitely repeated game as a risk game. We extend the definitions of risk strategies and risk strategy equilibrium to infinitely repeated games. We also research some properties of risk strategy equilibrium and show that players can obtain higher payoffs in risk strategy equilibrium than in pure strategy Nash equilibrium. / In multi-agent systems, agents often need to make decisions, especially under uncertainty. When a decision-maker needs to choose among a number of choices, each having a certain probability to happen, one of the traditional ways discussed in economics is to calculate the expected utility of each choice and choose the one with the maximum expected utility. However, most of the humans do not do so in real situations. Very often, humans choose a choice with a lower expected utility. One of the famous examples is the Allais paradox. / In strategic games, we define risk attitude and reputation, which are factors that decision-makers take into account in making decisions. We transform a strategic game to a risk game. We propose a new kind of strategies, called risk strategies. In the transformed risk game, we find a new kind of equilibrium, called risk strategy equilibrium. We also find out some properties of risk strategy equilibrium. In addition, we find that players can obtain higher payoffs in risk strategy equilibrium than in pure strategy Nash equilibrium. / One of the key properties defining an intelligent agent is social ability. This means that an intelligent agent should be able to interact with other agents or humans. Before designing an intelligent agent for any multi-agent system, we need to first understand how agents should behave and interact in that particular application. / One way to understand how agents should behave in a particular application is to model the application as a game. Besides, many real-life situations can be modeled as games. So, we extend the model of attractiveness maximization and apply the extended model to strategic games and infinitely repeated games. / The reason why most of the people do not maximize the expected utility is that people have different attitudes towards risk in different situations and people are generally risk-averse. To model this human behavior, we propose another way of decision-making, called attractiveness maximization. In this model, every choice has an attractiveness, which is calculated from the risk attitude of the decision-maker, probability, and utility. In making decisions, decision-makers choose the choice with the maximum attractiveness. Using attractiveness maximization, the phenomenon that human do not maximize expected utility can be explained. We also find some properties of the model of attractiveness maximization, which match the human behaviors. / We develop several applications of attractiveness maximization and risk strategies. First, we apply the proposed concepts to the Iterated Prisoner's Dilemma, which is widely used by economists and sociologists to model and simulate many of the human interactions. Simulation shows that agents have improved performance and are reactive as well as pro-active. Second, we construct behavioral predictors and an adaptive strategy for Minority Games, which model many real life situations like the financial market, auctions and resources competitions. Simulations show that the adaptive strategy works much better than previous models. Third, we model a resource allocation problem as a Minority Game and apply the behavioral predictors and the adaptive strategy to the resource allocation problem. Simulations also show that agents with the proposed adaptive strategy are able to make more right decisions and better resource utilization than previous work. / Lam, Ka Man. / "August 2007." / Adviser: Leung Ho Fung. / Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1107. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 159-173). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

Uma das principais motivações da Inteligência Artificial no contexto dos sistemas de entretenimento digital é criar personagens adaptáveis a novas situações, pouco previsíveis, com aprendizado rápido, memória de situações passadas e uma grande diversidade de comportamentos consistente e convincente ao longo do tempo. De acordo com recentes estudos desenvolvidos nos campos da Neurociência e da Psicologia, a capacidade de resolução de problemas não está unicamente atrelada à facilidade na manipulação de símbolos, mas também à exploração das características do ambiente e à interação social, que pode ser expressa na forma de fenômenos emocionais. Os resultados desses estudos confirmam o papel fundamental que cumprem a personalidade e as emoções nas atividades de percepção, planejamento, raciocínio, criatividade, aprendizagem, memória e tomada de decisão. Quando módulos para a manipulação de personalidade e emoções são incorporados à teoria de agentes, é possível a construção de Agentes com Comportamento Convincente (Believable Agents). O objetivo principal deste trabalho é desenvolver e implementar uma arquitetura de agentes inteligentes para construir personagens sintéticos cujos estados afetivos influenciam em suas atividades cognitivas. Para o desenvolvimento de tal arquitetura utilizou-se o modelo BDI (Beliefs, Desires e Intentions) como base e aos módulos existentes em uma implementação desse modelo foi incluído um Módulo Afetivo. Esse Módulo Afetivo é constituído por três submódulos (Personalidade, Humor e Emoção) e deve impactar nas atividades cognitivas de percepção, memória e tomada de decisão do agente. Duas provas de conceito (experimentos) foram construídas : a simulação do problema do ``Dilema do Prisioneiro Iterado\'\' e a versão computadorizada do ``Jogo da Memória\'\'. A construção desses experimentos permitiu avaliar empiricamente a influência da personalidade, humor e emoção nas atividades cognitivas dos agentes, e consequentemente no seu comportamento. Os resultados evidenciam que a utilização da nova arquitetura permite a construção de agentes com comportamentos mais coerentes, adaptativos e cooperativos quando comparados aos de agentes construídos com arquiteturas cujas atividades cognitivas não consideram o estado afetivo, e também produz um comportamento mais próximo de um agente humano que de um comportamento ótimo ou aleatório. Essa evidência de sucesso, apresentada nos resultados, mostra que os agentes construídos com a arquitetura proposta nessa dissertação indicam um avanço na direção do desenvolvimento dos Agentes com Comportamento Convincente. / One of the main motivations of Artificial Intelligence in the context of the digital entertainment systems is to create characters that are adaptable to new situations, unpredictable, fast learners, enable with memory of past situations and a variety of consistent and convincing behavior over time. According to recent studies conducted in the fields of Neuroscience and Psychology, the ability to solve problems is not only related to the capacity to manipulate symbols, but also to the ability to explore the environment and to engage into social interaction, which can be expressed as emotional phenomena. The results of these studies confirm the key role the personality and emotions play in the activities of perception, attention, planning, reasoning, creativity, learning, memory and decision making. When modules for handling personality and emotion, are incorporated in a theory of agents, it is possible to build Believable Agents. The main objective of this work is to develop and implement an intelligent agent architecture to build synthetic characters whose affective states influence their cognitive activities. To develop such architecture the BDI model (Beliefs, Desires and Intentions) was used as a basis, to which an Affective Module was included. The Affective Module consists of three sub-modules (Personality, Mood and Emotion), which influence the cognitive activities of perception, memory and decision making. Finally, two proofs of concept were built: the simulation of the problem of ``Iterated Prisoner\'s Dilemma\'\' and the computerized version of the ``Memory Game.\'\' The construction of these experiments allowed to evaluate empirically the influence of personality, mood and emotion in cognitive activities of agents and consequently in their behavior. The results show that using the proposed architecture one can build agents with more consistent, adaptive and cooperative behaviors when compared to agents built with architectures whose affective states do not influence their cognitive activities. It also produces a behavior that is closer to a human user than that of optimal or random behavior. This evidence of success, presented in the obtained results, show that agents built with the proposed architecture indicate an advance towards the development of Believable Agents.

Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-08-14T18:38:34Z No. of bitstreams: 1 ReinaldoSilva.pdf: 4540612 bytes, checksum: 7f60713fcfa6b7c9454af971170a8d47 (MD5) / Made available in DSpace on 2017-08-14T18:38:34Z (GMT). No. of bitstreams: 1 ReinaldoSilva.pdf: 4540612 bytes, checksum: 7f60713fcfa6b7c9454af971170a8d47 (MD5) Previous issue date: 2008-06-25 / The National Agency, Natural Gas and Biofuels, established the Program for Monitoring the Quality of Fuel Automotive, to evaluate continuously the quality of fuels and map the problems of non-compliance to standards. The research proposes the development of a system for monitoring the quality of fuel PASSI applying the methodology and techniques from artificial intelligence, using intelligent agents, and the JADE platform and language along with JESS Data Warehouse to create a repository of data that facilitates the management and support for decision-making of the Laboratory for Analysis and Research in Analytical Chemistry of Oil of the Federal University of Maranhão. / A Agência Nacional de Petróleo, Gás Natural e Biocombustíveis instituiu o Programa de Monitoramento da Qualidade de Combustíveis Automotivos, com o objetivo de avaliar permanentemente a qualidade dos combustíveis e mapear os problemas de não conformidade às normas estabelecidas. A pesquisa propõe o desenvolvimento de um sistema para o monitoramento da qualidade de combustíveis aplicando a metodologia PASSI e técnicas provenientes da Inteligência Artificial, utilizando agentes inteligentes, assim como a plataforma JADE e a linguagem JESS juntamente com Data Warehouse para criar um repositório de dados que facilite o gerenciamento e o apoio à tomada de decisão do Laboratório de Análise e Pesquisa em Química Analítica de Petróleo da Universidade Federal do Maranhão.