ACM AAAI Allen Newell Award
Stanford University United States – 2012
CITATION

For fundamental contributions at the intersection of computer science, game theory, and economics, most particularly in multi-agent systems and social coordination (broadly construed), which have yielded major contributions to all three disciplines.


Yoav Shoham and Moshe Tennenholtz have separately and jointly made significant contributions at the intersection of computer science, game theory, and economics, most particularly in multi-agent systems, social coordination, and related domains. Both are widely cited for seminal work in these areas. Yoav's pioneering work in agent-oriented programming provided a methodology for specifying distributed multi-agent systems, and his work in combinatorial auctions and mechanism design is equally foundational. Moshe created RMax  one of the best known reinforcement learning algorithms, and introduced the concept of program equilibrium to the analysis of Internet economies.

As collaborators, they have provided foundational contributions to the areas of social coordination, preceding the recent growth of activity in social networks. Their work established a framework for addressing coordination of multiple agents in distributed settings, and established a basis for examining a wide range of important questions and for developing influential applications in electronic commerce, combinatorial auctions, social computing, equilibrium computation, mechanism design, and multi-agent learning. Each has individually won the ACM SIGART Autonomous Agents Research Award for his own contributions to autonomous agents and multiagent systems.

Yoav and Moshe have also been influential in other areas. Yoavs textbook on multi-agent systems (with Kevin Leyton-Brown) is widely praised by key researchers from AI, operations research, philosophy, political science, economics and game theory, biology, and statistics. Moshe is acknowledged as a central contributor to many of Microsoft's pricing algorithms for online advertising. Both have served as program or general chairs for key conferences and on editorial boards of numerous journals. And both have trained impressive cohorts of students.

Press Release

Fellow
United States – 2012
CITATION

For contributions at the intersection of artificial intelligence, logic, and economics.

Yoav Shoham and Moshe Tennenholtz named recipients of the 2012 ACM/AAAI Allen Newell Award 

Yoav Shoham and Moshe Tennenholtz were recognized for contributions to multiagent systems spanning computer science, game theory, and economics. Shoham's pioneering work provided a methodology for specifying distributed multiagent systems. His research on game theory includes advances in combinatorial auctions, where participants place bids on combinations of discrete items. He also advanced mechanism design, sometimes known as reverse game theory, which sets formal rules that design a game as well as predicting how a game will be played. Shoham, professor of Computer Science at Stanford University, is a former director of Stanford's Artificial Intelligence Laboratory (SAIL), co-author (with Kevin Leyton-Brown) of Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, a widely-praised textbook on multiagent systems, and the founder of several e-commerce software companies.
 
Tennenholtz pioneered several approaches to the design and analysis of interactions between decision-makers in computational settings. He also created RMax, a general efficient algorithm applicable to learning by interacting with an environment. In addition, he introduced the concept of program equilibrium, an ingenious application of computer science to the analysis of Internet economies. He is acknowledged as a central contributor to many of Microsoft's pricing algorithms for online advertising.  He holds the Sondheimer Chair at the Technion - Israel Institute of Technology, and is a principal researcher at Microsoft Research Israel.