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Strategic negotiation in multiagent environmentsOctober 2001
Publisher:
  • MIT Press
  • 55 Hayward St.
  • Cambridge
  • MA
  • United States
ISBN:978-0-262-11264-2
Published:22 October 2001
Pages:
266
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Abstract

As computers advance from isolated workstations to linked elements in complex communities of systems and people, cooperation and coordination via intelligent agents become increasingly important. Examples of such communities include the Internet, electronic commerce, health institutions, electricity networks, and digital libraries.

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  3. Stryszowski M, Longo S, Velenis E and Forostovsky G (2021). A Framework for Self-Enforced Interaction Between Connected Vehicles: Intersection Negotiation, IEEE Transactions on Intelligent Transportation Systems, 22:11, (6716-6725), Online publication date: 1-Nov-2021.
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  5. Mezgebe T, Bril El Haouzi H, Demesure G, Pannequin R and Thomas A (2019). Multi-agent systems negotiation to deal with dynamic scheduling in disturbed industrial context, Journal of Intelligent Manufacturing, 31:6, (1367-1382), Online publication date: 1-Aug-2020.
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Contributors
  • Bar-Ilan University

Recommendations

Reviews

Jose M. Vidal

Two neighboring factories are taxed for the total amount of pollutants released every day. The amount of pollutants they each produce every day changes as a function of the orders they receive. The factories have two choices. They can either pay their tax as a proportion of the pollutants they emit every day, or they can negotiate each day to determine how much of the total tax each one will pay, and how many pollutants it will produce. For example, if one of the factories has a large production order that it must quickly fill, while the other one has a small production order with a flexible deadline, then the first factory will be more willing to pay more of the tax if this means it can engage in more production at an earlier date. In order to reach an agreement, both parties will need to engage in some form of strategic negotiation. These are the types of strategic negotiations studied in this book. In these negotiations, a group of selfish agents tries to reach an agreement that is beneficial to everyone and better than the alternative of not engaging in any negotiation. The book first presents a formal framework for describing and analyzing these types of conflicts. The following chapters analyze specific negotiation problems. The strategic negotiational model used in this book is based on Rubinstein’s model of alternating offers, where at each step, one agent makes a proposal that is either accepted by all, rejected by at least one agent, or discarded by an agent that opts out of the negotiation. If a situation occurs where either an agent opts out, or all agents accept the proposal, then the negotiation ends. Otherwise, the negotiation continues to the next step, where another agent makes a counter offer. The agents are assumed to have utility functions over the set of possible outcomes, including the opt-out outcome. These utility functions can change as a function of the time spent in negotiation. The book presents negotiation solutions that do not require a central decision maker, are symmetric in terms of the agents involved, use little negotiation time, reach an agreement whenever one exists, are simple to implement, and do not provide an incentive for any agent to deviate from the prescribed solution. After the introduction, each chapter studies a different negotiation problem. Chapter 3 deals with data allocation problems in which a set of selfish servers must decide how to allocate each incoming document. It assumes that the documents will not be duplicated and that the server must pay for storage, but receives payment whenever someone asks to see the document. Chapter 4 deals with a resource allocation problem where one agent is using a non-shareable resource and another agent desires to use the same resource. If the second agent opts out of the negotiation, it causes damage to the resource. The agents must negotiate over how long the first agent will use the resource. Chapter 5 extends the resource allocation problem to include the use of multiple attributes. Specifically, the agents negotiate over which specific time periods they will use the resource. Chapter 6 studies the problem of task distribution where agents must divide a set of equal tasks between them as they lose utility over time. That is, each agent would like all tasks to be done but would rather not have to do any itself, and loses utility as the tasks remain unassigned. Chapter 7 deals with pollution reduction scenarios like the one mentioned at the start of this review. Finally, chapter 8 deals with negotiations during a hostage crisis. Each of these problems is formalized by giving the agents specific utility functions, determining the set of possible agreements, and presenting negotiation strategies that reach those agreements under particular circumstances. The negotiation strategies are further validated by performing simulations. This book is an in-depth study of strategic negotiations analysis and design. The math is heavy at times, but the proofs can be safely skipped by readers who are merely interested in using the negotiation strategies presented. The book also offers many simple scenarios that help the reader understand the type of situations in which these strategies can be used. This is an excellent text for anyone interested in automated negotiations. Online Computing Reviews Service

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