DR-NEGOTIATE – A system for automated agent negotiation with defeasible logic-based strategies

Skylogiannis, Thomas; Antoniou, Grigoris; Bassiliades, Nick; Governatori, Guido; Bikakis, Antonis

doi:10.1016/j.datak.2007.03.004

Cited by 52 publications

(29 citation statements)

References 31 publications

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“…Although FIPA (Foundation for Intelligent Physical Agents) provides a plethora of protocols [14], such as FIPA brokering, FIPA English auctions, FIPA Contract net protocol, we found that there is no agreed upon standard interaction protocol for 1-1 automated negotiation. As a result, we adopt the negotiation protocol proposed by [45] and implemented by [41]. This protocol is a finite state machine that must be hard-coded in all agents participating into negotiation.…”

Section: Negotiation Protocolmentioning

confidence: 99%

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Knowledge-empowered agent information system for privacy payoff in eCommerce

et al. 2011

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Today, many online companies are gathering information and assembling sophisticated databases that know a great deal of information about many people, generally without the knowledge of those people. Such endeavor has resulted in the unprecedented attrition of individual's right to informational self-determination. On the one hand, Consumers are powerless to prevent the unauthorized dissemination of their personal information, and on the other, they are excluded from its profitable commercial exchange. This paper focuses on developing knowledge-empowered agent information system for privacy payoff as a means of rewarding consumers for sharing their personal information with online businesses. The design of this system is driven by the following argument: if consumers' personal information is a valuable asset, should they not be entitled to benefit from their asset as well? The proposed information system is a multi-agent system where several agents employ various knowledge and requirements for personal information valuation and interaction capabilities that most users cannot do on their own. The agents in the information system bear the responsibility of working on behalf of consumers to categorize their personal data objects, report to consumers on online businesses' trust and reputation, determine the value of their compensation using risk-based financial models, and finally negotiate for a payoff value in return for the dissemination of users' information. The details of the system as well as a proof-of-concept implementation using JADE (Java Agent Development Environment) are presented here.

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Section: Negotiation Protocolmentioning

confidence: 99%

“…While we understand that hard-coded protocols in agents may lead to inflexibility, the focus of this paper is not on protocol design but rather a negotiation strategy that maximizes the consumers' benefit. Following [41], our protocol is a finite state machine with discrete states and transition, see Fig. 5.…”

Section: Negotiation Protocolmentioning

confidence: 99%

Knowledge-empowered agent information system for privacy payoff in eCommerce

et al. 2011

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“…Another approach for building a system for automated agent negotiation incorporating defeasible logic is presented in [27]. It uses the JADE agent framework and declarative negotiation strategies implemented with the defeasible reasoning system DR-DEVICE.…”

Section: Related and Background Workmentioning

confidence: 99%

A knowledge-based framework for complex, proactive and service-oriented e-negotiation systems

Koumoutsos

Thramboulidis

2009

Electron Commer Res

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Advances in information technology and knowledge management change the way that e-negotiations, which constitute an important aspect of worldwide etrading, can be structured and represented. In this paper, a novel approach that focuses on knowledge modeling, formalization, representation and management in the domain of e-negotiation is described. The proposed approach exploits Ontologies, Service Oriented Architectures, Semantic Web Services, software agent platforms, and Knowledge-Bases to construct a framework that favors dynamically adapted negotiation protocols, negotiation process visualization and management, modeling and preference elicitation of the negotiated object and automatic deployment of negotiation interfaces. Negotiation process, protocol and strategy are examined, and a hybrid approach that integrates rules and workflow diagrams to describe and represent them is introduced.

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“…Defeasible Logic has been shown useful for application areas such as legal reasoning [12], modelling of agents and agent societies [13], agent negotiations [14], semantic brokering [15], and applications to the Semantic Web [8,9]. The paper is organised as follows.…”

Section: Introductionmentioning

confidence: 99%