Catálogo de publicaciones - libros

In this chapter, we study classification of combinatorial objects that are closely related to codes and designs. The objects considered can if fact in most cases be defined as certain codes or designs; algorithms and ideas from Chaps. 6 and 7 are then directly applicable.

In this chapter we present a framework for multi-agent system design which is based both on human organizational notions and principles for distributed intelligent systems design. The framework elaborates on the idea that notions from the field of organizational design can be used as the basis for the design of distributed intelligent systems. Organizational notions such as task, control, job, operation, management, coordination and organization are framed into an agent organizational framework. A collection of organizational design activities is presented that assists in a task oriented decomposition of the overall task of a system into jobs and the reintegration of jobs using job allocation, coordination mechanisms and organizational structuring. A number of coordination mechanisms have been defined in the organizational design literature. For the scope of this book we concentrate on: Direct Supervision where one individual takes all decisions for the work of others, Mutual Adjustment that achieves coordination by a process of informal communication between agents, and Standardization of Work, Output and Skills.

Three organizational structures are discussed, that coordinate agents and their work: Machine Bureaucracy, Professional Bureaucracy and Adhocracy. The Machine Bureaucracy is task-driven, seeing the organization as a single-purpose structure, which only uses one strategy to execute the overall task. The Professional Bureaucracy is competence-driven, where a part of the organization will first examine a case, match it to predetermined situations and then allocate specialized agents to it. In the Adhocracy the organization is capable of reorganizing its own structure including dynamically changing the work flow, shifting responsibilities and adapting to changing environments. A case study on distributed supply chain management shows the process from task decomposition via organizational design to three multi-agent architectures based on Mintzberg’s organizational structures. This chapter will be published in the International Journal of Human Computer Studies [van Aart, 2004].

In this chapter, we elaborate on the coordination perspectives of the organizational framework, introduced in Section 2.2.1 (p.12). The operational perspective is concerned with modeling technical activities performed by Operators. The coordination perspective is concerned with modeling coordination over these technical activities. In order to assist Managers in reasoning about coordination, strategies are represented in the form of problem-solving methods. Agents that need coordination, can agree to commit to one or more coordination strategies. Underlying the problem-solving methods is a coordination ontology that models the concepts and relationships describing the coordination domain. The coordination strategies are based on existing strategies, which were introduced in Section 2.2.3 (p.16). We report on a small experiment in which three coordination strategies were implemented as problem-solving methods in a multi-agent system.

The outcome of the experiment gives us observations concerning the appropriate use of coordination strategies. These observations are based on efficiency (the costs of communication and process time) and comparison between the strategies.

In this chapter we present the which is a conceptual framework for analyzing and designing the capabilities of an intelligent agent. The 5C model defines five dimensions of agent intelligence — using the notion of — where each dimension plays a role in the development of intelligent software agents. These dimensions are communication, competence, self, planner and environment. The company Bolesian B.V. first proposed the 5C model during an EU-funded project, called MARTRANS [van Aart et al., 2000]. From there it was developed as a part of internal Bolesian development projects and prototypes were built in Java and Delphi. Later it is was refined and used as professional agent analysis and design framework by Acklin B.V. to develop commercial applications. This chapter is partly based on two articles: co-authored by Kris van Marcke, published at the and co-authored by Kris van Marcke, published at .

This chapter is partly based on two deliverables of the IBROW project: D15 and D10 co-authored by B.J. Wielinga, A. Anjewierden and W. Jansweijer. The goal of the IBROW project (Intelligent Brokering on the Web, see http://ibrow.swi.psy.uva.nl) is to develop technologies for (semi-)automatic selection and configuration of new applications by reuse of existing services. Work on a multi-agent architecture capable of (semi-)automatic reuse of Problem-Solving Methods (PSMs) is discussed. Using the notion of separation of concerns, specialized agents are defined that operate within virtual environments. The agents within the architecture collaborate using specialized ontologies and collaboration patterns on top of an interoperability structure. A proof of concept is presented that explains the dynamics of parts of the architecture.

In this chapter we address the problem of how agents can handle message-based communication. Our approach is to look at ontology-based communication, in which the meaning and intention of messages is specified in message content ontologies. The idea is that agents can share semantics by committing to shared message content ontologies. We discuss a theoretical framework for message-based communication, in which we sketch an ideal world where an agent is capable of various ontological operations. A pragmatic approach is presented, which enables the creation and use of ontologies to support message-based communication between agents.

A tool is described that assists agent engineers in designing message content ontologies and export it to Java source code. A case study on Legal services illustrates conversations between agents based on a message content ontology. The work presented is partly based on the paper , published in Proceedings of the Workshop on Ontologies and Agent Systems at AAMAS 2002. The co-authors are R.F. Pels, G. Caire and F. Bergenti. The case study described is based on an Agentcities grant project (see www.acklin.nl/agentcities). The “Bean Generator” tool described is designed by the author and is used by various institutions and companies that work with the JADE toolkit (see http://gaper.swi.psy.uva.nl/beangenerator).

In this book, we studied the use of human organizational principles for multi-agent architecture design.We explored the use of division of labor and coordination as principles for multi-agent design, which resulted in a framework for agent organizational design (Chapter 2). Next, we investigated how agents can make use of coordination mechanisms which resulted in an interoperability framework that identifies the problems that arise when having heterogeneous agents collaborate with each other. A selection of alternatives to solve interoperability problems, i.e. coordination strategies and ontology-based communication has been discussed (Chapter 3, 5 and 6). Finally, we presented a conceptual agent model that takes into account the capabilities of an agent (Chapter 4).