Abstract. Agent architectures have to cope with a number of internal properties (concerns), such as autonomy, learning, and mobility. As the agent complexity increases, these agent properties crosscut each other and the agent’s basic functionality. In addition, multi-agent systems encompass multiple agent types with heterogeneous architectures. Each of these agent types has different properties, which need to be composed in different ways. In this context, the separation and the flexible composition of agent concerns are crucial for the construction of heterogeneous agent architectures. Moreover the separation of agent concerns needs to be guaranteed throughout the different development phases, especially from the architectural to the implementation phase. Existing approaches do not provide appropriate support for the modularization of agent properties at the architectural stage, and do not promote a smooth transition to the system implementation. This paper presents an aspect-oriented method that allows for a better separation of concerns, supporting the systematic aspectization of agent properties through the architectural definition, detailed design and implementation. A multi-agent system for paper reviewing management is assumed as a case study through this paper to show the applicability of our proposal. 1

To achieve the goal of realizing object adaptationto environments, a new role-based model Epsilon and a language EpsilonJ is proposed. In Epsilon, an environment is defined as a field of collaboration between roles and an object adapts to the environment assuming one of the roles. Objects can freely enter or leave environments and belong to multiple environments at a time so that dynamic adaptation or evolution of objects is realized. Environments and roles are the first class constructs at runtime as well as at model description time so that separation of concerns is not only materialized as a static structure but also observed as behaviors. Environments encapsulating collaboration are independent reuse components to be deployed separately from objects. In this paper, the Epsilon model and the language are explained with some examples. The effectiveness of the model is illustrated by a case study on the problem of integrated systems. Implementation of the language is also reported. 1.

Abstract. A programming construct mixin was invented to implement uniform extensions and modifications to classes. Although mixin-based programming has been extensively studied both on the methodological and theoretical point of views, relatively few attempts have been made on designing real programming languages that support mixins. In this paper, we address the issue of how to introduce a feature of declaring a mixin that may also be used as a type to nominally typed object-oriented languages like Java. We propose a programming language McJava, an extension of Java with mixin-types. To study type-soundness of McJava, we have formulated the core of McJava with typing and reduction rules, and proved its type-soundness. We also describe a compilation strategy of McJava that translates McJava programs to Java programs thus eventually making it runnable on standard Java virtual machines. 1

An intelligent agent has the ability to learn and adapt itself as a result of several events, including its own actions, its mistakes, its successive interactions with the external world and collaborations with other agents. As the agents ’ complexity increases, object-oriented abstractions cannot modularize the learning concern, which tends to spread across several system classes. This paper presents the Learning Aspect pattern, which documents an aspect-oriented solution for the separation of the learning concern, which in turn improves the system reusability and maintainability. Intent The Learning Aspect pattern modularizes the learning concern, totally decoupling the basic agent structure from the learning protocol. Context Engineers of intelligent agents [2, 3, 4] must deal with the agents ’ basic functionality, the agent services that are made available to the clients, and a number of additional concerns, such as learning, which greatly increase the system complexity. Agents need to learn based on internal and external events, including their own actions, their mistakes, the successive interactions with the external

Abstract: A number of concerns in Multiagent Systems (MAS) have a broadly-scoped impact on the system architectural decomposition, which in turn hinder the design of modular MAS architectures. Typical examples of crosscutting concerns in MAS architectures include learning, mobility, coordination, and autonomy. Nowadays there are some architectural proposals that envisage an emerging aspect-oriented architectural pattern as a potential solution to address modularity shortcomings of conventional architectural Copyright © 2008 Inderscience Enterprises Ltd. On the modularity assessment of aspect-oriented multiagent architectures 35 patterns for MAS designs. However, little effort has been dedicated to effectively assess when and which of these emerging and traditional architectural solutions promote in fact superior modularity in the presence of crosscutting MAS concerns. This paper presents a quantitative comparison between aspect-oriented and conventional MAS architectures. Our analysis evaluates how the architectures under comparison support the promotion of enhanced modularity in the presence of architectural crosscutting concerns in

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