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Internalising interaction protocols as first-class programming elements in multi agent systems
Author(s)
Advisor(s)
Date Issued
2012
Date Available
2015-08-27T09:17:40Z
Abstract
Since their inception, Multi Agent Systems (MASs) have been championed as a solution for the increasing problem of software complexity. Communities of distributed autonomous computing entities that are capable of collaborating, negotiating and acting to solve complex organisational and system management problems are an attractive proposition. Central to this is the requirement for agents to possess the capability of interacting with one another in a structured, consistent and organised manner.This thesis presents the Agent Conversation Reasoning Engine (ACRE), which constitutes a holistic view of communication management for MASs. ACRE is intended to facilitate the practical development, debugging and deployment of communication-heavy MASs.ACRE has been formally defined in terms of its operational semantics, and a generic architecture has been proposed to facilitate its integration with a wide variety of diverse agent development frameworks and Agent Oriented Programming (AOP) languages. A concrete implementation has also been developed that uses the Agent Factory AOP framework as its base. This allows ACRE to be used with a number of different AOP languages, while providing a reference implementation that other integrations can be modelled upon. A standard is also proposed for the modelling and sharing of agent-focused interaction protocols that is independent of the platform within which a concrete ACRE implementation is run.Finally, a user evaluation illustrates the benefits of incorporating conversation management into agent programming.
Type of Material
Doctoral Thesis
Publisher
University College Dublin. School of Computer Science and Informatics
Qualification Name
Ph.D.
Copyright (Published Version)
2012 the author
Web versions
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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Owning collection
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2440
Acquisition Date
Sep 14, 2024
Sep 14, 2024
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Sep 14, 2024