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Balancing conflict and cost in the selection of negotiation opponents

TLDR
In this article, a motivation-based opponent selection mechanism is used by a buyer-agent to evaluate and select between an already identified set of seller-agents in an agent-to-agent purchase negotiation.
Abstract
Within the context of agent-to-agent purchase negotiations, a problem that has received little attention is that of identifying negotiation opponents in situations where the consequences of conflict and the ability to access resources dynamically vary. Such dynamism poses a number of problems that make it difficult to automate the identification of appropriate opponents. To that end, this paper describes a motivation-based opponent selection mechanism used by a buyer-agent to evaluate and select between an already identified set of seller-agents. Sellers are evaluated in terms of the amount of conflict they are expected to bring to a negotiation and the expected amount of cost a negotiation with them entail. The mechanism allows trade-offs to be made between conflict and cost minimization, and experimental results show the effectiveness of the approach.

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Citations
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Predictive decision-making mechanisms based on off-line and on-line reasoning

TL;DR: Two predictive decision-making mechanisms are proposed that use the sequence of offers of both negotiating parties, up to the current negotiation stage, to predict the concession curve of the opponent.
References
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Journal ArticleDOI

Negotiation Decision Functions for Autonomous Agents

TL;DR: A formal model of negotiation between autonomous agents is presented, based on computationally tractable assumptions, demonstrated in the domain of business process management and empirically evaluated.
Journal ArticleDOI

Computational-mechanism design: a call to arms

TL;DR: This work states that game theory has developed powerful tools for analyzing, predicting, and controlling the behavior of self-interested agents and decision making in systems with multiple autonomous actors provide a foundation for building multiagent software systems.
Book ChapterDOI

A Framework for Argumentation-Based Negotiation

TL;DR: A general framework for negotiation in which agents exchange proposals backed by arguments which summarise the reasons why the proposals should be accepted is described.
Book

Understanding Agent Systems

TL;DR: The Z specification language is used to establish an accessible and unified formal account of agent systems and inter-agent relationships that provides precise and unambiguous meanings for common concepts and terms for agent systems.
Journal ArticleDOI

Social ReGreT, a reputation model based on social relations

TL;DR: How social network analysis techniques can be used to improve a reputation system and also how this system can be integrated with a negotiation model to increase the succes of negotiations are described.