Catálogo de publicaciones - libros
Agent-Oriented Software Engineering VII: 7th International Workshop, AOSE 2006, Hakodate, Japan, May 8, 2006, Revised and Invited Papers
Lin Padgham ; Franco Zambonelli (eds.)
En conferencia: 7º International Workshop on Agent-Oriented Software Engineering (AOSE) . Hakodate, Japan . May 8, 2006 - May 8, 2006
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Software Engineering/Programming and Operating Systems; Software Engineering; Artificial Intelligence (incl. Robotics); Logics and Meanings of Programs; Programming Techniques; Computer Communication Networks
Disponibilidad
Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
---|---|---|---|---|
No detectada | 2007 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-540-70944-2
ISBN electrónico
978-3-540-70945-9
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2007
Información sobre derechos de publicación
© Springer-Verlag Berlin Heidelberg 2007
Tabla de contenidos
Monitoring Group Behavior in Goal-Directed Agents Using Co-efficient Plan Observation
Jan Sudeikat; Wolfgang Renz
Purposeful, time– and cost–oriented engineering of Multi–Agent Systems (MAS) requires developers to understand the relationships between the numerous behaviors exhibited by individual agents and the resulting global MAS behavior. While development methodologies have drawn attention to verification and debugging of single agents, software producing organizations need to validate that the MAS, as a cooperative system exhibiting group behavior, is behaving as expected. Recent research has proposed techniques to infer mathematical descriptions of macroscopic MAS behavior from microscopic reactive and adaptive agent behaviors. In this paper, we show how similar descriptions can be adjusted to MAS composed of goal–directed agent architectures. We argue that goal–hierarchies found in Requirements Engineering and Belief Desire Intention (BDI) architectures are suitable data structures to facilitate a stochastic modeling approach. To enable monitoring of agent behaviors, we introduce an enhancement to the well-known capability concept for BDI agents. So-called co–efficient capabilities are a novel approach to modularize crosscutting concerns in BDI agent implementations. A case study applies co–efficient plan observation to exemplify and confirm our modeling approach.
- Testing, Debugging and Evolvability | Pp. 174-189
Evaluating a Model Driven Development Toolkit for Domain Experts to Modify Agent Based Systems
Gaya Buddhinath Jayatilleke; Lin Padgham; Michael Winikoff
An agent oriented approach is well suited for complex application domains, and often when such applications are used by domain experts they identify modifications to be made to these applications. However, domain experts are usually limited in agent programming knowledge, and are not able to make these changes themselves. The aim of this work is to provide support so that domain experts are able to make modifications to agent systems. In this paper we report on an evaluation of our Component Agent Framework for domain Experts (CAFnE) framework and toolkit, giving a detailed account of a usability study we conducted with a group of experienced meteorologists.
- Testing, Debugging and Evolvability | Pp. 190-207
Building the Core Architecture of a NASA Multiagent System Product Line
Joaquin Peña; Michael G. Hinchey; Antonio Ruiz-Cortés; Pablo Trinidad
The field of Software Product Lines (SPL) emphasizes building a family of software products from which concrete products can be derived rapidly. This helps to reduce time-to-market, costs, etc., and can result in improved software quality and safety. Current Agent-Oriented Software Engineering (AOSE) methodologies are concerned with developing a single Multiagent System. The main contribution of this paper is a proposal to developing the core architecture of a Multiagent Systems Product Line (MAS-PL), exemplifying our approach with reference to a concept NASA mission based on multiagent technology.
- Testing, Debugging and Evolvability | Pp. 208-224