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Recent Advances in Agent-based Complex Automated Negotiation

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Cover of 'Recent Advances in Agent-based Complex Automated Negotiation'

Table of Contents

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    Book Overview
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    Chapter 1 Prediction of the Opponent’s Preference in Bilateral Multi-issue Negotiation Through Bayesian Learning
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    Chapter 2 Automated Negotiating Agent with Strategy Adaptation for Multi-times Negotiations
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    Chapter 3 Optimal Non-adaptive Concession Strategies with Incomplete Information
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    Chapter 4 Handling Agents’ Incomplete Information in a Coalition Formation Model
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    Chapter 5 A Multiagent Multilateral Negotiation Protocol for Joint Decision-Making
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    Chapter 6 On the Complexity of Utility Hypergraphs
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    Chapter 7 Negotiations in Holonic Multi-agent Systems
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    Chapter 8 Recent Advances in Agent-based Complex Automated Negotiation
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    Chapter 9 A Performance Optimization Support Framework for GPU-Based Traffic Simulations with Negotiating Agents
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    Chapter 10 RECON: A Robust Multi-agent Environment for Simulating COncurrent Negotiations
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    Chapter 11 Using Transfer Learning to Model Unknown Opponents in Automated Negotiations
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    Chapter 12 Gaussian-Based Bidding Strategies for Service Composition Simulations
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    Chapter 13 The Fifth Automated Negotiating Agents Competition (ANAC 2014)
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    Chapter 14 GANGSTER: An Automated Negotiator Applying Genetic Algorithms
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    Chapter 15 AgentM
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    Chapter 16 k-GAgent: Negotiating Agents Considering Interdependencies Between Issues
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    Chapter 17 A Greedy Coordinate Descent Algorithm for High-Dimensional Nonlinear Negotiation
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    Chapter 18 DoNA—A Domain-Based Negotiation Agent
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    Chapter 19 WhaleAgent: Hardheaded Strategy and Conceder Strategy Based on the Heuristics
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    Chapter 20 Agent YK: An Efficient Estimation of Opponent’s Intention with Stepped Limited Concessions
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    Chapter 21 BraveCat: Iterative Deepening Distance-Based Opponent Modeling and Hybrid Bidding in Nonlinear Ultra Large Bilateral Multi Issue Negotiation Domains
Attention for Chapter 21: BraveCat: Iterative Deepening Distance-Based Opponent Modeling and Hybrid Bidding in Nonlinear Ultra Large Bilateral Multi Issue Negotiation Domains
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Chapter title
BraveCat: Iterative Deepening Distance-Based Opponent Modeling and Hybrid Bidding in Nonlinear Ultra Large Bilateral Multi Issue Negotiation Domains
Chapter number 21
Book title
Recent Advances in Agent-based Complex Automated Negotiation
Published by
Springer, Cham, January 2016
DOI 10.1007/978-3-319-30307-9_21
Book ISBNs
978-3-31-930305-5, 978-3-31-930307-9
Authors

Farhad Zafari, Faria Nassiri-Mofakham, Zafari, Farhad, Nassiri-Mofakham, Faria

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Other 1 13%
Professor 1 13%
Student > Master 1 13%
Researcher 1 13%
Other 1 13%
Unknown 1 13%
Readers by discipline Count As %
Computer Science 6 75%
Business, Management and Accounting 1 13%
Unknown 1 13%