scholarly journals Intelligent Agents for Automatic Service Composition in Ambient Intelligence

Author(s):  
Maria J. ◽  
Francisco Moya ◽  
Felix J. ◽  
David Villa ◽  
Juan C.
2008 ◽  
Vol 29 (3-4) ◽  
pp. 265-276 ◽  
Author(s):  
Maria J. Santofimia ◽  
Francisco Moya ◽  
Felix J. Villanueva ◽  
David Villa ◽  
Juan C. Lopez

2012 ◽  
Vol 4 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Maria J. Santofimia ◽  
Xavier del Toro ◽  
Felix J. Villanueva ◽  
Jesus Barba ◽  
Francisco Moya ◽  
...  

The incapability to foresee or react to all the events that take place in a specific environment supposes an important handicap for Ambient Intelligence systems, expected to be self-managed, proactive, and goal-driven. Endowing such systems with capabilities to understand and reason about context seems like a promising solution to overcome this hitch. Supported on the service-oriented paradigm, composing rather than combining services provides a reasonable mean to implement versatile systems. This paper describes how systems for Ambient Intelligence can be improved by combining automatic service composition and reasoning capabilities upon a distributed middleware framework.


Author(s):  
Nabeel Azam ◽  
Vasa Curcin ◽  
Li Guo ◽  
Moustafa Ghanem

Workflow systems play an important role in service-oriented computing as they provide an intuitive mechanism for orchestrating the execution of remote services. Constructing new workflows from raw services however, is not always a straight-forward task. It requires resolving many decisions including locating available services, determining which of them match the user requirements and also deciding how to compose them together into valid applications. Workflow construction activities can be simplified, or possibly even automated, by using a combination of semantic annotations and delegation of the decision making tasks to intelligent agents. Two key challenges arise when developing a practical system that attempts to address this vision. The first is elaborating the key properties of service workflows and the decisions that agents are required to assist in. This information is needed for designing and implementing the internals of the agent mind. The second is designing and implementing the run-time interfaces between the workflow system and the agent system to enable the exchange of information between them. This chapter describes our experience in addressing these two challenges and in developing a framework that simplifies the workflow creation process within the ARGUGRID project.


2013 ◽  
Vol 756-759 ◽  
pp. 2120-2124
Author(s):  
Shan Zhou ◽  
Fang Yu Zhang

The paper proposes a method for semantic message matching in automatic service composition. It develops a framework in which the exported message description and behavior description of a service, and represents the behavior of a service with a finite state machine. Since the service interface definition can be represented by ontology concepts, the internal representation language enables us to define some issues required by service composition formally, qualitative and quantitative constraints plus reasoning on concepts, and the service behavior can be represented using linear logic formulas, so the inference rules of linear logic can check the match-ability and satisfy-ability of service message.


Author(s):  
Mihai Horia Zaharia

Highly developed economies are based on the knowledge society. A variety of software tools are used in almost every aspect of human life. Service-oriented architectures are limited to corporate-related business solutions. This chapter proposes a novel approach aimed to overcome the differences between real life services and software services. Using the design approaches for the current service-oriented architecture, a solution that can be implemented in open source systems has been proposed. As a result, a new approach to creating an agent for service composition is introduced. The agent itself is created by service composition too. The proposed approach might facilitate the research and development of Web services, service-oriented architectures, and intelligent agents.


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