3 research outputs found
An Analysis Architecture for Communications in Multi-agent Systems
Evaluation tools are significant from the Agent
Oriented Software Engineering (AOSE) point of view. Defective
designs of communications in Multi-agent Systems (MAS) may
overload one or several agents, causing a bullying effect on them.
Bullying communications have avoidable consequences, as high
response times and low quality of service (QoS). Architectures
that perform evaluation functionality must include features to
measure the bullying activity and QoS, but it is also
recommendable that they have reusability and scalability
features. Evaluation tools with these features can be applied to a
wide range of MAS, while minimizing designer’s effort. This
work describes the design of an architecture for communication
analysis, and its evolution to a modular version, that can be
applied to different types of MAS. Experimentation of both
versions shows differences between its executions
Realizing networks of proactive smart products
The sheer complexity and number of functionalities embedded in many everyday devices already exceed the ability of most users to learn how to use them effectively. An approach to tackle this problem is to introduce ‘smart’ capabilities in technical products, to enable them to proactively assist and co-operate with humans and other products. In this paper we provide an overview of our approach to realizing networks of proactive and co-operating smart products, starting from the requirements imposed by real-world scenarios. In particular, we present an ontology-based approach to modeling proactive problem solving, which builds on and extends earlier work in the knowledge acquisition community on problem solving methods. We then move on to the technical design aspects of our work and illustrate the solutions, to do with semantic data management and co-operative problem solving, which are needed to realize our functional architecture for proactive problem solving in concrete networks of physical and resource-constrained devices. Finally, we evaluate our solution by showing that it satisfies the quality attributes and architectural design patterns, which are desirable in collaborative multi-agents systems
An experimental investigation of profiler and recommender agent in the context of knowledge sharing facilitation
This article aims to collect user satisfaction to prove whether user profiling and recommendation is significant in
knowledge sharing facilitation framework. A four-factor evaluation metric to measure the overall performance of the agent based system
is used.The evaluation metric consists
of three types of analysis which are overlap analysis, weighted responds analysis and responds analysis. The four-factor metric covers the efficiency of user profile built
by the agent, the relevance of recommendation, the staff directory and the document repository.The main discussion
is on the setting of the experiment and the results of KSFaci performance in the proposed experiment setting.It is concluded that user profiling and recommendation plays a role in knowledge sharing system framework