Modeling and programming with commitment rules in agent factory

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Title: Modeling and programming with commitment rules in agent factory
Authors: Collier, Rem
O'Hare, G. M. P. (Greg M. P.)
Permanent link: http://hdl.handle.net/10197/3541
Date: 2009
Abstract: Agent-Oriented Programming (AOP) is a relatively new programming paradigm introduced by Yoav Shoham (1993) in which software systems are viewed as consisting of a set of agents that interact with one another to solve problems that are beyond their individual capabilities. More specifically, agents are viewed as high-level autonomous software entities that encapsulate a set of capabilities and whose internal state is comprised of a set of mental components such as beliefs, capabilities, choices and commitments. This view of agents as mentalistic entities is a common perspective within multi-agent systems research and underpins many of the most prominent agent theories (Cohen & Levesque, 1990; Rao & Georgeff, 1991; Wooldridge, 2000). These theories model the internal decision-making process of an agent in terms of the interplay between the constituent components of the underlying mental state. Their objective is to define how an agent is able to act in a rational goal-directed manner and to tease out various desirable properties that emerge from that action. Thus, the objective of AOP is to present a framework for developing a new class of programming languages that are derived from these theories.
Funding Details: Science Foundation Ireland
Type of material: Book Chapter
Publisher: IGI Global
Copyright (published version): Copyright 2009, IGI Global
Keywords: Agent-oriented programmingMulti-agent systemsDecision-makingProgramming languages
Subject LCSH: Computer programming
Multiagent systems
Decision making
Programming languages (Electronic computers)
Language: en
Status of Item: Peer reviewed
Is part of: Giurca, A., Gasevic, D., Taveter, K. (eds.). Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches
Appears in Collections:Computer Science Research Collection

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