Author Description

--> 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