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

Implementation of context-aware workflows with Multi-agent Systems

Systems in Ambient Intelligence (AmI) need to manage workflows that represent users’ activities. These workflows can be quite complex, as they may involve multiple participants, both physical and computational, playing different roles. Their execution implies monitoring the development of the activities in the environment, and taking the necessary actions for them and the workflow to reach a certain end. The context-aware approach supports the development of these applications to cope with event processing and regarding information issues. Modeling the actors in these context-aware workflows, where complex decisions and interactions must be considered, can be achieved with multi-agent systems. Agents are autonomous entities with sophisticated and flexible behaviors, which are able to adapt to complex and evolving environments, and to collaborate to reach common goals. This work presents architectural patterns to integrate agents on top of an existing context-aware architecture. This allows an additional abstraction layer on top of context-aware systems, where knowledge management is performed by agents.This approach improves the flexibility of AmI systems and facilitates their design. A case study on guiding users in buildings to their meetings illustrates this approach

Behaviour Driven Development for Multi-Agent Systems

This paper presents a testing methodology to apply Behaviour Driven Development (BDD) techniques while developing Multi-Agent Systems (MAS), so called BEhavioural Agent Simple Testing (BEAST) methodology. It is supported by the developed open source framework (BEAST Tool) which automatically generates test cases skeletons from BDD scenarios specifications. The developed framework allows testing MASs based on JADE or JADEX platforms and offers a set of configurable Mock Agents which allow the execution of tests while the system is under development. BEAST tool has been validated in the development of a MAS for fault diagnosis in FTTH (Fiber To The Home) networks

Checking consistency of agent designs against interaction protocols for early-phase defect location

Multi-agent systems are increasingly being used in complex applications due to features such as autonomy, proactivity, exibility, robustness and social ability. However, these very features also make verifying multi-agent systems a challeng- ing task. In this paper, we propose a mechanism, including automated tool support, for early phase defect detection by comparing agent interaction speci cations with the detailed design of the agents participating in the interactions. The basic intuition of our approach is to extract sets of possi- ble traces from the agent design and to verify whether these traces conform to the protocol speci cations. Our approach is based on the Prometheus agent design methodology but is applicable to other similar methodologies. Our initial eval- uation shows that even simple protocols developed by rela- tively experienced developers are prone to defects, and our approach is successful in uncovering some of these defects

Engineering Multiagent Systems - Reflections

This report documents the programme and outcomes of Dagstuhl Seminar 12342 ``Engineering multiagent Systems\u27\u27. The seminar brought together researchers from both academia and industry to identify the potential for and facilitate convergence towards standards for agent technology. As such it was particularly relevant to industrial research. A key objective of the seminar, moreover, has been to establish a road map for engineering multiagent systems. Various research areas have been identified as important topics for a research agenda with a focus on the development of multiagent systems. Among others, these include the integration of agent technology and legacy systems, component-based agent design, standards for tooling, establishing benchmarks for agent technology, and the development of frameworks for coordination and organisation of multiagent systems. This report presents a more detailed discussion of these and other research challenges that were identified. The unique atmosphere of Dagstuhl provided the perfect environment for leading researchers from a wide variety of backgrounds to discuss future directions in programming languages, tools and platforms for multiagent systems, and the road map produced by the seminar will have a timely and decisive impact on the future of this whole area of research

An Approach for the Qualitative Analysis of Open Agent Conversations

This paper presents an approach for the qualitative analysis of data obtained from past communicative interactions in an open multiagent system. Such qualitative analysis focuses on the use of high-level agent communication languages to infer theories about agents with mental states which are normally not accessible for the outside observer. The inference of these theories, or context models, is based on logging semantic data available from protocol execution traces and using this information as samples for the application of data mining algorithms. These context models can be applied both by system developers and agents themselves at run-time for various tasks, e.g. to predict future agent behaviour, to support the process of ontological alignment in communication, or to assess the trustworthiness of agents. An implementation of the approach presented is also given, the ProtocolMiner tool, which automates the building of context models from arbitrary protocol executions

Adapting Agent Platforms to Web Service Environments

This master thesis tries to address the above-mentioned issues by creating an agent plat- form suitable for encapsulating web-services into agents, providing them with typical agent capabilities (such as learning or complex communication and reasoning mechanisms). The objective of this point is to create a generic, modular agent platform that is able to run lightweight agents. The agents should be able to easily invoke web-services, e ectively encapsulating them. They also should be able to easily coordinate for composing the invoked services in order to perform complex tasks. Thus, the platform must provide facilities to allow the agents perform these service invocations

Software Language Engineering: Interaction and Usability Modeling of Language Editors

Background: Domain-Specific Languages (DSLs) are programming languages created to a specific domain that a user has pre-conceived. Multi-Agent Systems (MAS) represent a set of systems interacting within an environment, in which many intelligent agents interact with each other. Usability is a property of something that is "capable of being used"and "convenient and practicable for use". Barišic et al. introduced a conceptual framework that supports the iterative development process of DSLs concerning the usability evaluation. Semantic Web Enabled Agent Modeling Language (SEA_ML) is a DSL that supports the modeling and generation of action-based systems for MAS and the Semantic Web. It is defined by 44 visual notations. Objective: Improve SEA_ML’s usability using "The "Physics"of Notations" principles to create a new visual notation for SEA_ML. Method: (1) Participants test the current notation and the new notation on four exercises. For each exercise, a SUS questionnaire is presented. Participants should have better results on the exercises with the new notation. (2) Participants select the notations for SEA_ML. Participants receive a list with figures including the current and the new notation, alongside a set of descriptions for each of the semantic constructs of SEA_ML. Participants should select more icons from the new notation. Results: With the results gathered from each experience it is not clear that the new visual notations are better than the current notations. Limitation: The results from the guidelines were not evaluated broadly. Conclusion: The results for each experiment are not clear that the new notation is better than the current notation. This thesis is part of a scientific and technological co-operation between NOVA LINCS research center at Universidade Nova de Lisboa, Portugal, and Ege University International Computer Institute, Turkey. regarding the project Developing a Framework on Evaluating Domain specific Modeling Languages for Multi-Agent Systems