Publications are sorted into categories by topic:
Mechanism Design for Data Science
See the list of publications in the MDDS website.
Agent Perspective and Reinforcement Learning
R-max-a general polynomial time algorithm for near-optimal reinforcement learning. RI Brafman, M Tennenholtz. Journal of Machine Learning Research 3 (Oct), 213-231
Efficient learning equilibrium. RI Brafman, M Tennenholtz. Advances in Neural Information Processing Systems 15
Learning to coordinate efficiently: A model-based approach. RI Brafman, M Tennenholtz. Journal of Artificial Intelligence Research 19, 11-23
Adaptive load balancing: A study in multi-agent learning. A Schaerf, Y Shoham, M Tennenholtz. Journal of artificial intelligence research 2, 475-500
Encouraging physical activity in patients with diabetes: intervention using a reinforcement learning system. E Yom-Tov, G Feraru, M Kozdoba, S Mannor, M Tennenholtz, I Hochberg. Journal of medical Internet research 19 (10), e7994
Dueling algorithms. N Immorlica, AT Kalai, B Lucier, A Moitra, A Postlewaite, M Tennenholtz. Proceedings of the forty-third annual ACM symposium on Theory of computing.
Competitive safety analysis: Robust decision-making in multi-agent systems. M Tennenholtz. Journal of Artificial Intelligence Research 17, 363-378
Playing Games without Observing Payoffs. Michal Feldman, Adam Kalai, Moshe Tennenholtz
Mastering multi-player games. Yossi Azar, Michal Feldman, Uriel Feige, Moshe Tennenholtz.
On partially controlled multi-agent systems. RI Brafman, M Tennenholtz. Journal of Artificial Intelligence Research 4, 477-507
On planning while learning. S Safra, M Tennenholtz. Journal of Artificial Intelligence Research 2, 111-129
Mediator Perspective and Social Laws
On social laws for artificial agent societies: Off-line design. Y Shoham, M Tennenholtz. Artificial Intelligence 73 (1-2), 231-252
Determination of social laws for multi-agent mobilization. S Onn, M Tennenholtz. Artificial Intelligence 95 (1), 155-167
Off-line reasoning for on-line efficiency. Y Moses, M Tennenholtz. IJCAI, 490-495
Artificial social systems. Y Moses, M Tennenholtz. Computers and Artificial Intelligence 14, 533-562.
On stable social laws and qualitative equilibria. M Tennenholtz. Artificial Intelligence 102 (1), 1-20
Choosing social laws for multi-agent systems: Minimality and simplicity. D Fitoussi, M Tennenholtz. Artificial Intelligence 119 (1-2), 61-101
On the emergence of social conventions: modeling, analysis, and simulations. Y Shoham, M Tennenholtz. Artificial Intelligence 94 (1-2), 139-166
Emergent conventions in multi-agent systems: initial experimental results and observations (preliminary report). Y Shoham, M Tennenholtz. Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning
Strong mediated equilibrium. D Monderer, M Tennenholtz. Artificial Intelligence 173 (1), 180-195
Routing Mediators. O Rozenfeld, M Tennenholtz. IJCAI, 1488-1493
Mediators in position auctions. I Ashlagi, D Monderer, M Tennenholtz. Games and Economic Behavior 67 (1), 2-21
k-Implementation. D Monderer, M Tennenholtz. Journal of Artificial Intelligence Research 21, 37-62
On the value of correlation. I Ashlagi, D Monderer, M Tennenholtz. Journal of Artificial Intelligence Research 33, 575-613
Program equilibrium. M Tennenholtz. Games and Economic Behavior 49 (2), 363-373
A game-theoretic approach to recommendation systems with strategic content providers. O Ben-Porat, M Tennenholtz. Advances in Neural Information Processing Systems 31
Economic recommendation systems. G Bahar, R Smorodinsky, M Tennenholtz. arXiv preprint arXiv:1507.07191
The Axiomatic Approach
Ranking systems: the PageRank axioms. A Altman, M Tennenholtz. Proceedings of the 6th ACM conference on Electronic commerce, 1-8
Trust-based recommendation systems: an axiomatic approach. R Andersen, C Borgs, J Chayes, U Feige, A Flaxman, A Kalai, V Mirrokni, M Tennenholtz. Proceedings of the 17th international conference on World Wide Web, 199-208
Axiomatic foundations for ranking systems. A Altman, M Tennenholtz. Journal of Artificial Intelligence Research 31, 473-495
An axiomatic approach to personalized ranking systems. A Altman, M Tennenholtz. Journal of the ACM (JACM) 57 (4), 1-35
Incentive compatible ranking systems. A Altman, M Tennenholtz. Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
On the foundations of qualitative decision theory. RI Brafman, M Tennenholtz. Proceedings of the national conference on artificial intelligence, 1291-1296
Mechanisms for multi-level marketing. Y Emek, R Karidi, M Tennenholtz, A Zohar. Proceedings of the 12th ACM conference on Electronic commerce, 209-218
Modeling agents as qualitative decision makers. RI Brafman, M Tennenholtz. Artificial Intelligence 94 (1-2), 217-268
An axiomatic treatment of three qualitative decision criteria. RI Brafman, M Tennenholtz. Journal of the ACM (JACM) 47 (3), 452-482
Approximate Mechanism Design without Money
Approximate mechanism design without money. AD Procaccia, M Tennenholtz. ACM Transactions on Economics and Computation (TEAC) 1 (4), 1-26
Approximately optimal mechanism design via differential privacy. K Nissim, R Smorodinsky, M Tennenholtz. Proceedings of the 3rd innovations in theoretical computer science conference
Strategyproof approximation of the minimax on networks. N Alon, M Feldman, AD Procaccia, M Tennenholtz. Mathematics of Operations Research 35 (3), 513-526
Sum of us: Strategyproof selection from the selectors. N Alon, F Fischer, A Procaccia, M Tennenholtz. Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge
Distributed Games and Non-cooperative Computing
Distributed games: From mechanisms to protocols. D Monderer, M Tennenholtz. AAAI/IAAI 99, 32-37
Distributed games. D Monderer, M Tennenholtz. Games and Economic Behavior 28 (1), 55-72
Non-cooperative computation: Boolean functions with correctness and exclusivity. Y Shoham, M Tennenholtz. Theoretical Computer Science 343 (1-2), 97-113
Overcoming free riding in multi-party computations—The anonymous case. R Smorodinsky, M Tennenholtz. Games and Economic Behavior 55 (2), 385-406
Congestion games with failures. M Penn, M Polukarov, M Tennenholtz. Proceedings of the 6th ACM Conference on Electronic Commerce, 259-268
Strong and correlated strong equilibria in monotone congestion games. O Rozenfeld, M Tennenholtz. International Workshop on Internet and Network Economics, 74-86
Fault tolerant mechanism design. R Porter, A Ronen, Y Shoham, M Tennenholtz. Artificial Intelligence 172 (15), 1783-1799
Fair imposition. R Porter, Y Shoham, M Tennenholtz. Journal of Economic Theory 118 (2), 209-228
On cooperation in a multi-entity model: Preliminary report. M Tennenholtz, Y Moses. Proceedings of the 11th international joint conference on Artificial intelligence
Electronic Commerce and Marketing
Signaling schemes for revenue maximization. Y Emek, M Feldman, I Gamzu, R PaesLeme, M Tennenholtz
Position auctions with budgets: Existence and uniqueness. I Ashlagi, M Braverman, A Hassidim, R Lavi, M Tennenholtz. Berkeley Electronic Press
Optimizing budget allocation among channels and influencers. N Alon, I Gamzu, M Tennenholtz. Proceedings of the 21st international conference on World Wide Web, 381-388
Bundling equilibrium in combinatorial auctions. R Holzman, N Kfir-Dahav, D Monderer, M Tennenholtz. Games and Economic Behavior 47 (1), 104-123