Interactions in Multiagent Systems
eBook - ePub

Interactions in Multiagent Systems

  1. 332 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Interactions in Multiagent Systems

About this book

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This compendium covers several important topics related to multiagent systems, from learning and game theoretic analysis, to automated negotiation and human-agent interaction. Each chapter is written by experienced researchers working on a specific topic in mutliagent system interactions, and covers the state-of-the-art research results related to that topic.

The book will be a good reference material for researchers and graduate students working in the area of artificial intelligence/machine learning, and an inspirational read for those in social science, behavioural economics and psychology.

--> Sample Chapter(s)
Chapter 1: Scalability of Multiagent Reinforcement Learning --> Contents:

  • Scalability of Multiagent Reinforcement Learning (Yunkai Zhuang, Yujing Hu and Hao Wang)
  • Centralization or Decentralization? A Compromising Solution Toward Coordination in Multiagent Systems (Chao Yu, Hongtao Lv, Hongwei Ge, Liang Sun, Jun Meng and Bingcai Chen)
  • Making Efficient Reputation-Aware Decisions in Multiagent Systems (Han Yu, Chunyan Miao, Bo An, Zhiqi Shen and Cyril Leung)
  • Decision-Theoretic Planning in Partially Observable Environments (Zongzhang Zhang and Mykel Kochenderfer)
  • Multiagent Reinforcement Learning Algorithms Based on Gradient Ascent Policy (Chengwei Zhang, Xiaohong Li, Zhiyong Feng and Wanli Xue)
  • Task Allocation in Multiagent Systems: A Survey of Some Interesting Aspects (Jun Wu, Lei Zhang, Yu Qiao and Chongjun Wang)
  • Automated Negotiation: An Efficient Approach to Interaction Among Agents (Siqi Chen and Gerhard Weiss)
  • Norm Emergence in Multiagent Systems (Tianpei Yang, Jianye Hao, Zhaopeng Meng and Zan Wang)
  • Diffusion Convergence in the Collective Interactions of Large-scale Multiagent Systems (Yichuan Jiang, Yifeng Zhou, Fuhan Yan and Yunpeng Li)
  • Incorporating Inference into Online Planning in Multiagent Settings (Yingke Chen, Prashant Doshi, Jing Tang and Yinghui Pan)

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--> Readership: Researchers, academics, professionals and graduate students in artificial intelligence and machine learning. -->
Multiagent System;Game-Theoretic Analysis;Automated Negotiation;Human-Agent Interaction;Social Network Analysis;Norm Emergence00

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Yes, you can access Interactions in Multiagent Systems by Jianye Hao, Ho-Fung Leung in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Title
  3. Copyright
  4. Foreword
  5. About the Editors
  6. About the Contributors
  7. Contents
  8. 1. Scalability of Multiagent Reinforcement Learning
  9. 2. Centralization or Decentralization? A Compromising Solution Toward Coordination in Multiagent Systems
  10. 3. Making Efficient Reputation-Aware Decisions in Multiagent Systems
  11. 4. Decision-Theoretic Planning in Partially Observable Environments
  12. 5. Multiagent Reinforcement Learning Algorithms Based on Gradient Ascent Policy
  13. 6. Task Allocation in Multiagent Systems: A Survey of Some Interesting Aspects
  14. 7. Automated Negotiation: An Efficient Approach to Interaction Among Agents
  15. 8. Norm Emergence in Multiagent Systems
  16. 9. Diffusion Convergence in the Collective Interactions of Large-scale Multiagent Systems
  17. 10. Incorporating Inference into Online Planning in Multiagent Settings
  18. Bibliography
  19. Index