955 resultados para principal-agent-problem


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Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made individually. In Group Decision Argumentation, there is a set of participants, with different profiles and expertise levels, that exchange ideas or engage in a process of argumentation and counter-argumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this paper, it is proposed a Multi-Agent simulator for the behaviour representation of group members in a decision making process. Agents behave depending on rational and emotional intelligence and use persuasive argumentation to convince and make alternative choices.

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This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

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Emotion although being an important factor in our every day life it is many times forgotten in the development of systems to be used by persons. In this work we present an architecture for a ubiquitous group decision support system able to support persons in group decision processes. The system considers the emotional factors of the intervenient participants, as well as the argumentation between them. Particular attention will be taken to one of components of this system: the multi-agent simulator, modeling the human participants, considering emotional characteristics, and allowing the exchanges of hypothetic arguments among the participants.

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As the time goes on, it is a question of common sense to involve in the process of decision making people scattered around the globe. Groups are created in a formal or informal way, exchange ideas or engage in a process of argumentation and counterargumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this work it is proposed an agent-based architecture to support a ubiquitous group decision support system, i.e. based on the concept of agent, which is able to exhibit intelligent, and emotional-aware behaviour, and support argumentation, through interaction with individual persons or groups. It is enforced the paradigm of Mixed Initiative Systems, so the initiative is to be pushed by human users and/or intelligent agents.

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Group decision making plays an important role in organizations, especially in the present-day economy that demands high-quality, yet quick decisions. Group decision-support systems (GDSSs) are interactive computer-based environments that support concerted, coordinated team efforts toward the completion of joint tasks. The need for collaborative work in organizations has led to the development of a set of general collaborative computer-supported technologies and specific GDSSs that support distributed groups (in time and space) in various domains. However, each person is unique and has different reactions to various arguments. Many times a disagreement arises because of the way we began arguing, not because of the content itself. Nevertheless, emotion, mood, and personality factors have not yet been addressed in GDSSs, despite how strongly they influence results. Our group’s previous work considered the roles that emotion and mood play in decision making. In this article, we reformulate these factors and include personality as well. Thus, this work incorporates personality, emotion, and mood in the negotiation process of an argumentbased group decision-making process. Our main goal in this work is to improve the negotiation process through argumentation using the affective characteristics of the involved participants. Each participant agent represents a group decision member. This representation lets us simulate people with different personalities. The discussion process between group members (agents) is made through the exchange of persuasive arguments. Although our multiagent architecture model4 includes two types of agents—the facilitator and the participant— this article focuses on the emotional, personality, and argumentation components of the participant agent.

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Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

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This paper aims to present a multi-agent model for a simulation, whose goal is to help one specific participant of multi-criteria group decision making process.This model has five main intervenient types: the human participant, who is using the simulation and argumentation support system; the participant agents, one associated to the human participant and the others simulating the others human members of the decision meeting group; the directory agent; the proposal agents, representing the different alternatives for a decision (the alternatives are evaluated based on criteria); and the voting agent responsiblefor all voting machanisms.At this stage it is proposed a two phse algorithm. In the first phase each participantagent makes his own evaluation of the proposals under discussion, and the voting agent proposes a simulation of a voting process.In the second phase, after the dissemination of the voting results,each one ofthe partcipan agents will argue to convince the others to choose one of the possible alternatives. The arguments used to convince a specific participant are dependent on agent knowledge about that participant. This two-phase algorithm is applied iteratively.

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With the increasing importance of large commerce across the Internet it is becoming increasingly evident that in a few years the Iternet will host a large number of interacting software agents. a vast number of them will be economically motivated, and will negociate a variety of goods and services. It is therefore important to consider the economic incentives and behaviours of economic software agents, and to use all available means to anticipate their collective interactions. This papers addresses this concern by presenting a multi-agent market simulator designed for analysing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms, consideting risk preferences. The system includes agents that are capable of increasing their performance with their own experience, by adapting to the market conditions. The results of the negotiations between agents are analysed by data minig algorithms in order to extract rules that give agents feedback to imprive their strategies.

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Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made just by one individual. The simulation of group decision making through a Multi-Agent System is a very interesting research topic. The purpose of this paper it to specify the actors involved in the simulation of a group decision, to present a model to the process of group formation and to describe the approach made to implement that model. In the group formation model it is considered the existence of incomplete and negative information, which was identified as crucial to make the simulation closer to the reality.

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The main goal of this work is to solve mathematical program with complementarity constraints (MPCC) using nonlinear programming techniques (NLP). An hyperbolic penalty function is used to solve MPCC problems by including the complementarity constraints in the penalty term. This penalty function [1] is twice continuously differentiable and combines features of both exterior and interior penalty methods. A set of AMPL problems from MacMPEC [2] are tested and a comparative study is performed.

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Mathematical Program with Complementarity Constraints (MPCC) finds many applications in fields such as engineering design, economic equilibrium and mathematical programming theory itself. A queueing system model resulting from a single signalized intersection regulated by pre-timed control in traffic network is considered. The model is formulated as an MPCC problem. A MATLAB implementation based on an hyperbolic penalty function is used to solve this practical problem, computing the total average waiting time of the vehicles in all queues and the green split allocation. The problem was codified in AMPL.

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The paper discusses the difficulties in judging the quality of scientific manuscripts and describes some common pitfalls that should be avoided when preparing a paper for submission to a peer-reviewed journal. Peer review is an imperfect system, with less than optimal reliability and uncertain validity. However, as it is likely that it will remain as the principal process of screening papers for publication, authors should avoid some common mistakes when preparing a report based on empirical findings of human research. Among these are: excessively long abstracts, extensive use of abbreviations, failure to report results of parsimonious data analyses, and misinterpretation of statistical associations identified in observational studies as causal. Another common problem in many manuscripts is their excessive length, which makes them more difficult to be evaluated or read by the intended readers, if published. The evaluation of papers after their publication with a view towards their inclusion in a systematic review is also discussed. The limitations of the impact factor as a criterion to judge the quality of a paper are reviewed.

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A Obesidade é considerada um grave problema de saúde pública, com consequências negativas para os indivíduos obesos, nomeadamente dificuldades no desempenho de atividades de vida diária, na locomoção e na prática de exercício físico, o que pode restringir a participação em atividades sociais e de lazer. Esta investigação consiste num estudo quantitativo descritivo e tem como objetivo principal descrever de que forma os indivíduos adultos obesos classificam a sua adaptação ocupacional, a partir dos conceitos de identidade e competência ocupacional. Com este estudo, pretende-se ainda verificar se os indivíduos obesos apresentam níveis de atividade física mais baixos e valores mais elevados de pressão plantar, em relação a indivíduos com peso normal. A amostra é constituída por dez indivíduos adultos, de ambos os sexos, com índice de massa corporal igual (IMC) ou superior a 30 Kg/m2, e os instrumentos de avaliação utilizados são o Questionário Ocupacional (adaptado por N. Riopel com assistência de G. Kielhofner e J. Hawkins Watts – 1986), o IPAQ – Versão Curta e o Sistema de Palmilhas Pedar. A partir dos resultados, pode-se verificar que os indivíduos obesos apresentam uma rotina diária em que a maioria das atividades realizadas está relacionada com a casa, o trabalho e o descanso e que a percentagem de atividades de lazer em que participam é reduzida. No entanto, parecem satisfeitos com o seu desempenho na maior parte das atividades, consideram que muitas delas são importantes para si e estão motivados para as realizar. Dos resultados obtidos, podemos sugerir que os indivíduos obesos apresentam boa adaptação ocupacional. Pode-se ainda dizer que os indivíduos obesos apresentam um baixo nível de intensidade de atividade física, não se observando diferenças significativas relativamente aos indivíduos com peso normativo e que os seus valores máximos de pressão plantar normalizados são inferiores quando comparados com a população de peso normal.

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Dissertação de Mestrado, Ambiente, Saúde e Segurança, 18 de Fevereiro de 2011, Universidade dos Açores.