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Aviv Zohar

Hebrew University of Jerusalem

Aviv Zohar is a senior lecturer at the School of Engineering and Computer

Science in the Hebrew University of Jerusalem and he is a Golda Meir Fellow. His postdoctoral work was at Microsoft Research. Zohar has a PhD in computer science from the Hebrew University. His other honors include an award of excellence from the Israeli Knesset and the committee of university heads, a Leibniz scholarship during his PhD studies, and a scholarship from the Wolf Foundation during his MSc. Contact him at avivz@cs.huji.ac.il.

A I ’ s 1 0 t o W at c h

Incentives in Multiagent Systems

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esigners of multiagent systems set rules by defining their underlying ­protocols that define both the basic language of interaction and the behav-

ior that agents should adopt. For example, TCP defines the format of messages that are sent but also asks communicating parties to lower the rate of data transmission if too many packets are lost (this is done to keep the network uncongested). Due to the system’s distributed nature and each participant’s autonomy, there’s no way to strictly enforce such behavior. Agents that gain from deviating from the prescribed behavior can do so, and the system behaves quite differently than initially expected. In the case of TCP congestion control, deviating from the protocol can cause a congestion collapse that drastically slows down all traffic passing through the network. My research is aimed at analyzing the incentives of agents in such systems using tools from AI, game theory, and economics. I seek to create protocols in which the recommended behavior is

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also the best course of action for each participant without compromising other properties such as system efficiency or robustness. Along with my various collaborators, I’ve explored a wide range of compu­ tational systems including core Internet communication protocols such as Border Gateway Protocol (BGP) and TCP, where communicating parties might attempt to gain more bandwidth or a more desirable path through the network. These foundational protocols, while imperfect, have interesting incentive structures that help explain their adoption. In other systems such as peer-to-peer file sharing (where participants typically lack the incentives to upload files to others), incentive issues hinder wider adoption. My work has focused on the

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partial improvements of current protocols such as BitTorrent and on exploring the market-like ad hoc solutions that filesharing communities have adopted. Finally, novel distributed open systems such as the crypto-currency Bitcoin continue to emerge, bringing with them new challenges. One of Bitcoin’s main strengths is in its incentives for nodes that authorize transactions. The transaction fees awarded to these nodes have attracted many to join Bitcoin’s network and to invest their computing resources in securing it. On the other hand, competition for these very fees, which is expected to increase in the future, could cause profitmaximizing nodes to behave in ways that damage the system. I continue to work on ways to improve the protocol before such problems are encountered. The Internet’s rise and the prevalence of computing devices promise that innovative and exciting multiagent systems will continue to appear and that multiagent systems research will continue to flourish.

IEEE INTELLIGENT SYSTEMS

31/07/13 9:21 PM

IEEE Intelligent Systems AI's 10 to Wach 2013  
IEEE Intelligent Systems AI's 10 to Wach 2013  

Every two years, IEEE Intelligent Systems acknowledges and celebrates 10 young stars in the field of AI as “AI's 10 to Watch.” These accompl...

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