Resumo em Inglês:

The organizational design of a distributed system defines how entities act and interact to achieve local and global objectives. We describe how a system employing different types of organizational techniques has been used to address the challenges posed by a distributed sensor network environment. The high-level, multi-agent architecture of this realworld system is given in detail, and we provide empirical results demonstrating the effects the organization has on the system's performance across several different metrics. As with any design, the particular approach that is employed makes trade-offs, some of which are obvious and some more subtle. The presence of such trade-offs motivates the need for a better understanding of precisely how the organization influences large and small-scale behaviors. To address this need, we first demonstrate how a collection of analytic models can be developed to predict such effects. This experience is then used to ground the presentation of a more comprehensive, domain-independent organizational modeling language called ODML. The structure and capabilities of ODML are explained through the construction of a unified model of our sensor network organization. We then show that this model provides an accurate prediction of the original empirical results.

Resumo em Inglês:

This paper introduces systems of exchange values as tools for the organization of multi-agent systems. Systems of exchange values are defined on the basis of the theory of social exchanges, developed by Piaget and Homans. A model of social organization is proposed, where social relations are construed as social exchanges and exchange values are put into use in the support of the continuity of the performance of social exchanges. The dynamics of social organizations is formulated in terms of the regulation of exchanges of values, so that social equilibrium is connected to the continuity of the interactions. The concept of supervisor of social equilibrium is introduced as a centralized mechanism for solving the problem of the equilibrium of the organization The equilibrium supervisor solves such problem making use of a qualitative Markov Decision Process that uses numerical intervals for the representation of exchange values.

Resumo em Inglês:

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. Designing appropriate KM processes and enabling technology face considerable risks, as they must be shaped to respond to specific needs of the organizational environment. Thus, many systems are abandoned or fall into disuse because of inadequate understanding of the organizational context. This motivates current research, which tends to propose agent organizations as a useful paradigm for KM systems engineering. Following these approaches, organizations are analyzed as collective systems, composed of several agents, each of them autonomously producing and managing their own local data according to their own logic, needs, and interpretative schema, i.e. their goals and beliefs. These agents interact and coordinate for goal achievement defining a coherent local knowledge system. This paper presents a novel methodology for analyzing the requirements of a KM system based on an iterative workflow where a pivotal role is played by agent-oriented modeling. Within this approach, the needs for KM systems are traced back to the organization stakeholders' goals. A case study is used to illustrate the methodology. The relationship of this work with current studies in agent organizations and organizational knowledge management is also discussed. Differently from other works, this methodology aims at offering a practical guideline to the analyst, pointing out the appropriate abstractions to be used in the different phases of the analysis.

Resumo em Inglês:

One of the well studied issues in multi-agent systems is the standard action-selection problem where a goal task can be performed in different ways, by different agents. Also the sequence of these actions can influence the goal achievement or its quality. This class of problems has been tackled under different approaches. At the high-level coordination one, the specification of the organizational issues is crucial. However, in dynamic environments, agents must be able to adapt to the changing organizational goals, available resources, their relationships to the presence of another agents, and so on. This problem is a key one in multi-agent systems and relates to models of learning and adaptation, such as those observed among social insects. The present paper tackles the process of generating, adapting, and changing multi-agent organization dynamically at system runtime, using a swarm inspired approach. This approach is used here mainly for task allocation with low need of pre-planning and specification, and no need of explicit coordination. The results of our approach and another quantitative one are compared here and it is shown that in dynamic domains, the agents adapt to changes in the organization, just as social insects do.

Resumo em Inglês:

Virtual organization refers to the temporary teaming of enterprises. By sharing physical, human and knowledge resources via information technologies, a virtual organization enables member enterprises to share skills, costs, access to one another's markets and, at the same time decrease the risk of investments. To realize this new generation of business model, the ability to form and operate virtual enterprise is very important. The paper describes our experience gained by implementing a multiagent system that simulates an artificial marketplace, for which we have derived several decision-making mechanisms in various stages of a virtual organization. We presented a negotiation protocol and a bid selection algorithm for agents to form a virtual organization. We adopted the Motivational Quantities framework to support the agent's local reasoning process. In order to better understand the organizational problem, we adapted a statistical model that predicts the expected rewards of individual agents and the performance of the virtual organization. The comparison and analysis of the results from both the simulation and the model prediction are also presented in this paper.