# Moshe Tennenholtz's research while affiliated with Technion - Israel Institute of Technology and other places

## Publications (343)

Preprint
Full-text available
We study the costs and benefits of selling data to a competitor. Although selling all consumers' data may decrease total firm profits, there exist other selling mechanisms---in which only some consumers' data is sold---that render both firms better off. We identify the profit-maximizing mechanism, and show that the benefit to firms comes at a cost...
Preprint
Full-text available
We study an information design problem with two informed senders and a receiver in which, in contrast to traditional Bayesian persuasion settings, senders do not have commitment power. In our setting, a trusted mediator/platform gathers data from the senders and recommends the receiver which action to play. We characterize the set of implementable...
Preprint
Full-text available
A celebrated known cognitive bias of individuals is that the pain of losing is psychologically higher than the pleasure of gaining. In robust decision making under uncertainty, this approach is typically associated with the selection of safety (aka security) level strategies. We consider a refined notion, which we term loss aversion, capturing the...
Chapter
A data curator would like to collect data from privacy-aware agents. The collected data will be used for the benefit of all agents. Can the curator incentivize the agents to share their data truthfully? Can he guarantee that truthful sharing will be the unique equilibrium? Can he provide some stability guarantees on such equilibrium? We study neces...
Chapter
This paper studies cooperative data-sharing between competitors vying to predict a consumer’s tastes. We design optimal data-sharing schemes both for when they compete only with each other, and for when they additionally compete with an Amazon—a company with more, better data. We show that simple schemes—threshold rules that probabilistically induc...
Preprint
Full-text available
A data curator would like to collect data from privacy-aware agents. The collected data will be used for the benefit of all agents. Can the curator incentivize the agents to share their data truthfully? Can he guarantee that truthful sharing will be the unique equilibrium? Can he provide some stability guarantees on such equilibrium? We study neces...
Conference Paper
Conference Paper
Preprint
Full-text available
We study the effects of data sharing between firms on prices, profits, and consumer welfare. Although indiscriminate sharing of consumer data decreases firm profits due to the subsequent increase in competition, selective sharing can be beneficial. We show that there are data-sharing mechanisms that are strictly Pareto-improving, simultaneously inc...
Article
Sender-receiver interactions, and specifically persuasion games, are widely researched in economic modeling and artificial intelligence, and serve as a solid foundation for powerful applications. However, in the classic persuasion games setting, the messages sent from the expert to the decision-maker are abstract or well-structured application-spec...
Preprint
Full-text available
Commercial entries, such as hotels, are ranked according to score by a search engine or recommendation system, and the score of each can be improved upon by making a targeted investment, e.g., advertising. We study the problem of how a principal, who owns or supports a set of entries, can optimally allocate a budget to maximize their ranking. Repre...
Article
Full-text available
Persuasion games are fundamental in economics and AI research and serve as the basis for important applications. However, work on this setup assumes communication with stylized messages that do not consist of rich human language. In this paper we consider a repeated sender (expert) – receiver (decision maker) game, where the sender is fully informe...
Preprint
Full-text available
The quality of learning generally improves with the scale and diversity of data. Companies and institutions can therefore benefit from building models over shared data. Many cloud and blockchain platforms, as well as government initiatives, are interested in providing this type of service. These cooperative efforts face a challenge, which we call "...
Preprint
In competitive search settings such as the Web, many documents' authors (publishers) opt to have their documents highly ranked for some queries. To this end, they modify the documents - specifically, their content - in response to induced rankings. Thus, the search engine affects the content in the corpus via its ranking decisions. We present a fir...
Article
Weighted voting games apply to a wide variety of multi-agent settings. They enable the formalization of power indices which quantify the coalitional power of players. We take a novel approach to the study of the power of big vs. small players in these games. We model small (big) players as having single (multiple) votes. The aggregate relative powe...
Conference Paper
Weighted voting games are applicable to a wide variety of multi-agent settings. They enable the formalization of power indices which quantify the coalitional power of players. We take a novel approach to the study of the power of big vs.~small players in these games. We model small (big) players as having single (multiple) votes. The aggregate rela...
Article
A population of voters must elect representatives among themselves to decide on a sequence of possibly unforeseen binary issues. Voters care only about the final decision, not the elected representatives. The disutility of a voter is proportional to the fraction of issues, where his preferences disagree with the decision. While an issue-by-issue vo...
Conference Paper
Preprint
Full-text available
Weighted voting games apply to a wide variety of multi-agent settings. They enable the formalization of power indices which quantify the coalitional power of players. We take a novel approach to the study of the power of big vs. small players in these games. We model small (big) players as having single (multiple) votes. The aggregate relative powe...
Article
The recent literature on fair Machine Learning manifests that the choice of fairness constraints must be driven by the utilities of the population. However, virtually all previous work makes the unrealistic assumption that the exact underlying utilities of the population (representing private tastes of individuals) are known to the regulator that i...
Preprint
Full-text available
Persuasion games are fundamental in economics and AI research and serve as the basis for important applications. However, work on this setup assumes communication with stylized messages that do not consist of rich human language. In this paper we consider a repeated sender (expert) -- receiver (decision maker) game, where the sender is fully inform...
Preprint
Sender-receiver interactions, and specifically persuasion games, are widely researched in economic modeling and artificial intelligence, and serve as a solid foundation for powerful applications. However, in the classic persuasion games setting, the messages sent from the expert to the decision-maker are abstract or well-structured application-spec...
Preprint
Full-text available
Masking tokens uniformly at random constitutes a common flaw in the pretraining of Masked Language Models (MLMs) such as BERT. We show that such uniform masking allows an MLM to minimize its training objective by latching onto shallow local signals, leading to pretraining inefficiency and suboptimal downstream performance. To address this flaw, we...
Conference Paper
The connection between messaging and action is fundamental both to web applications, such as web search and sentiment analysis, and to economics. However, while prominent online applications exploit messaging in natural (human) language in order to predict non-strategic action selection, the economics literature focuses on the connection between st...
Preprint
Full-text available
A population of voters must elect representatives among themselves to decide on a sequence of possibly unforeseen binary issues. Voters care only about the final decision, not the elected representatives. The disutility of a voter is proportional to the fraction of issues, where his preferences disagree with the decision. While an issue-by-issue vo...
Preprint
Full-text available
A recent body of work addresses safety constraints in explore-and-exploit systems. Such constraints arise where, for example, exploration is carried out by individuals whose welfare should be balanced with overall welfare. In this paper, we adopt a model inspired by recent work on a bandit-like setting for recommendations. We contribute to this lin...
Preprint
Given a directed forest-graph, a probabilistic \emph{selection mechanism} is a probability distribution over the vertex set. A selection mechanism is \emph{incentive-compatible} (IC), if the probability assigned to a vertex does not change when we alter its outgoing edge (or even remove it). The quality of a selection mechanism is the worst-case ra...
Preprint
The ranking incentives of many authors of Web pages play an important role in the Web dynamics. That is, authors who opt to have their pages highly ranked for queries of interest, often respond to rankings for these queries by manipulating their pages; the goal is to improve the pages' future rankings. Various theoretical aspects of this dynamics h...
Article
The connection between messaging and action is fundamental both to web applications, such as web search and sentiment analysis, and to economics. However, while prominent online applications exploit messaging in natural (human) language in order to predict non-strategic action selection, the economics literature focuses on the connection between st...
Preprint
The Web is a canonical example of a competitive retrieval setting where many documents' authors consistently modify their documents to promote them in rankings. We present an automatic method for quality-preserving modification of document content -- i.e., maintaining content quality -- so that the document is ranked higher for a query by a non-dis...
Preprint
Full-text available
This paper studies cooperative data-sharing between competitors vying to predict a consumer's tastes. We design optimal data-sharing schemes both for when they compete only with each other, and for when they additionally compete with an Amazon---a company with more, better data. In both cases we show that participants benefit from such coopetition....
Article
A recurring theme in recent computer science literature is that proper design of signaling schemes is a crucial aspect of effective mechanisms aiming to optimize social welfare or revenue. One of the research endeavors of this line of work is understanding the algorithmic and computational complexity of designing efficient signaling schemes. In rea...
Preprint
The connection between messaging and action is fundamental both to web applications, such as web search and sentiment analysis, and to economics. However, while prominent online applications exploit messaging in natural (human) language in order to predict non-strategic action selection, the economics literature focuses on the connection between st...
Article
VCG is a classical combinatorial auction that maximizes social welfare. However, while the standard single-item Vickrey auction is false-name-proof, a major failure of multi-item VCG is its vulnerability to false-name attacks. This occurs already in the natural bare minimum model in which there are two identical items and bidders are single-minded....
Article
We investigate the possibility of an incentive-compatible (IC, a.k.a. strategy-proof) mechanism for the classification of agents in a network according to their reviews of each other. In the α-classification problem we are interested in selecting the top α fraction of users. We give upper bounds (impossibilities) and lower bounds (mechanisms) on th...
Article
It is widely observed that individuals prefer to interact with others who are more similar to them (this phenomenon is termed homophily). This similarity manifests itself in various ways such as beliefs, values and education. Thus, it should not come as a surprise that when people make hiring choices, for example, their similarity to the candidate...
Article
We consider social learning where agents can only observe part of the population (modeled as neighbors on an undirected graph), face many decision problems, and arrival order of the agents is unknown. The central question we pose is whether there is a natural observability graph that prevents the information cascade phenomenon. We introduce the ‘ce...
Article
Novel approaches draw on the strength of game theoretic mechanism design.
Preprint
We investigate the possibility of an incentive-compatible (IC, a.k.a. strategy-proof) mechanism for the classification of agents in a network according to their reviews of each other. In the $\alpha$-classification problem we are interested in selecting the top $\alpha$ fraction of users. We give upper bounds (impossibilities) and lower bounds...
Preprint
Full-text available
VCG is a classical combinatorial auction that maximizes social welfare. However, while the standard single-item Vickrey auction is false-name-proof, a major failure of multi-item VCG is its vulnerability to false-name attacks. This occurs already in the natural bare minimum model in which there are two identical items and bidders are single-minded....
Article
Exclusive social groups are ones in which the group members decide whether or not to admit a candidate to the group. Examples of exclusive social groups include academic departments and fraternal organizations. In this article, we introduce an analytic framework for studying the dynamics of exclusive social groups. In our model, every group member...
Article
Full-text available
We discuss voting scenarios in which the set of voters (agents) and the set of alternatives are the same; that is, voters select a single representative from among themselves. Such a scenario happens, for instance, when a committee selects a chairperson, or when peer researchers select a prize winner. Our model assumes that each voter either render...
Article
Full-text available
We consider a game-theoretic model of information retrieval with strategic authors. We examine two different utility schemes: authors who aim at maximizing exposure and authors who want to maximize active selection of their content (i.e., the number of clicks). We introduce the study of author learning dynamics in such contexts. We prove that under...
Preprint
Full-text available
People increasingly turn to the Internet when they have a medical condition. The data they create during this process is a valuable source for medical research and for future health services. However, utilizing these data could come at a cost to user privacy. Thus, it is important to balance the perceived value that users assign to these data with...
Conference Paper
Prediction is a well-studied machine learning task, and prediction algorithms are core ingredients in online products and services. Despite their centrality in the competition between online companies who offer prediction-based products, the strategic use of prediction algorithms remains unexplored. The goal of this paper is to examine strategic us...
Conference Paper
Full-text available
Technological evolution, so central to the progress of humanity in recent decades, is the process of constantly introducing new technologies to replace old ones. A new technology does not necessarily mean a better technology and so should not always be embraced. How can society learn which novelties present actual improvements over the existing tec...
Preprint
Full-text available
Machine Learning (ML) algorithms shape our lives. Banks use them to determine if we are good borrowers; IT companies delegate them recruitment decisions; police apply ML for crime-prediction, and judges base their verdicts on ML. However, real-world examples show that such automated decisions tend to discriminate protected groups. This generated a...
Preprint
Full-text available
Recommendation systems often face exploration-exploitation tradeoffs: the system can only learn about the desirability of new options by recommending them to some user. Such systems can thus be modeled as multi-armed bandit settings; however, users are self-interested and cannot be made to follow recommendations. We ask whether exploration can neve...
Preprint
Full-text available
Prediction is a well-studied machine learning task, and prediction algorithms are core ingredients in online products and services. Despite their centrality in the competition between online companies who offer prediction-based products, the \textit{strategic} use of prediction algorithms remains unexplored. The goal of this paper is to examine str...
Article
Full-text available
Facility location games have been a topic of major interest in economics, operations research, and computer science, starting from the seminal work by Hotelling [Hotelling H (1929) Stability in competition. Econom. J. 39(153):41–57]. In the classical pure location Hotelling game, businesses compete for maximizing customer attraction by strategicall...
Preprint
Full-text available
Behavioral decision theories aim to explain human behavior. Can they help predict it? An open tournament for prediction of human choices in fundamental economic decision tasks is presented. The results suggest that integration of certain behavioral theories as features in machine learning systems provides the best predictions. Surprisingly, the mos...
Article
Full-text available
Recommendation systems are extremely popular tools for matching users and contents. However, when content providers are strategic, the basic principle of matching users to the closest content, where both users and contents are mod-eled as points in some semantic space, may yield low social welfare. This is due to the fact that content providers are...
Conference Paper
Full-text available
Preprint
Recommendation systems are extremely popular tools for matching users and contents. However, when content providers are strategic, the basic principle of matching users to the closest content, where both users and contents are modeled as points in some semantic space, may yield low social welfare. This is due to the fact that content providers are...
Article
Richman games are zero-sum games, where in each turn players bid in order to determine who will play next (Lazarus et al., 1999). We extend the theory to impartial general-sum two player games called bidding games, showing the existence of pure subgame-perfect equilibria (PSPE). In particular, we show that PSPEs form a semilattice, with a unique an...
Preprint
We analyse strategic, complete information, sequential voting with ordinal preferences over the alternatives. We consider several voting mechanisms: plurality voting and approval voting with deterministic or uniform tie-breaking rules. We show that strategic voting in these voting procedures may lead to a very undesirable outcome: Condorcet winning...
Preprint
We discuss voting scenarios in which the set of voters (agents) and the set of alternatives are the same; that is, voters select a single representative from among themselves. Such a scenario happens, for instance, when a committee selects a chairperson, or when peer researchers select a prize winner. Our model assumes that each voter either render...
Preprint
Full-text available
Modern recommendation systems rely on the wisdom of the crowd to learn the optimal course of action. This induces an inherent mis-alignment of incentives between the system's objective to learn (explore) and the individual users' objective to take the contemporaneous optimal action (exploit). The design of such systems must account for this and als...
Preprint
We consider a game-theoretic model of information retrieval with strategic authors. We examine two different utility schemes: authors who aim at maximizing exposure and authors who want to maximize active selection of their content (i.e. the number of clicks). We introduce the study of author learning dynamics in such contexts. We prove that under...
Preprint
For many queries in the Web retrieval setting there is an on-going ranking competition: authors manipulate their documents so as to promote them in rankings. Such competitions can have unwarranted effects not only in terms of retrieval effectiveness, but also in terms of ranking robustness. A case in point, rankings can (rapidly) change due to smal...
Preprint
Prediction is a well-studied machine learning task, and prediction algorithms are core ingredients in online products and services. Despite their centrality in the competition between online companies who offer prediction-based products, the strategic use of prediction algorithms remains unexplored. The goal of this paper is to examine strategic us...
Preprint
We introduce a game-theoretic approach to the study of recommendation systems with strategic content providers. Such systems should be fair and stable. Showing that traditional approaches fail to satisfy these requirements, we propose the Shapley mediator. We show that the Shapley mediator satisfies the fairness and stability requirements, runs in...
Preprint
Full-text available
Data driven segmentation is the powerhouse behind the success of online advertising. Various underlying challenges for successful segmentation have been studied by the academic community, with one notable exception - consumers incentives have been typically ignored. This lacuna is troubling as consumers have much control over the data being collect...
Preprint
We formalize the current practice of strategic mining in multi-cryptocurrency markets as a game, and prove that any better-response learning in such games converges to equilibrium. We then offer a reward design scheme that moves the system configuration from any initial equilibrium to a desired one for any better-response learning of the miners. Ou...
Preprint
Our work bridges the literature on incentive-compatible mechanism design and the literature on diffusion algorithms. We introduce the study of finding an incentive-compatible (strategy-proof) mechanism for selecting an influential vertex in a directed graph (e.g. Twitter's network). The goal is to devise a mechanism with a bounded ratio between the...
Conference Paper
Users of social networks often focus on specific areas of that network, leading to the well-known "filter bubble" effect. Connecting people to a new area of the network in a way that will cause them to become active in that area could help alleviate this effect and improve social welfare. Here we present preliminary analysis of network referrals, t...
Conference Paper
Our work bridges the literature on incentive-compatible mechanism design and the literature on diffusion algorithms. We introduce the study of finding an incentive-compatible (strategy-proof) mechanism for selecting an influential vertex in a directed graph (e.g. Twitter»s network). The goal is to devise a mechanism with a bounded ratio between the...
Article
The main goal of search engines is ad hoc retrieval: ranking documents in a corpus by their relevance to the information need expressed by a query. The Probability Ranking Principle (PRP) — ranking the documents by their relevance probabilities — is the theoretical foundation of most existing ad hoc document retrieval methods. A key observation tha...
Conference Paper
Facility location games have been a topic of major interest in economics, operations research and computer science, starting from the seminal work by Hotelling. Spatial facility location models have successfully predicted the outcome of competition in a variety of scenarios. In a typical facility location game, users/customers/voters are mapped to...
Article
Full-text available
Background Regular physical activity is known to be beneficial for people with type 2 diabetes. Nevertheless, most of the people who have diabetes lead a sedentary lifestyle. Smartphones create new possibilities for helping people to adhere to their physical activity goals through continuous monitoring and communication, coupled with personalized f...
Article
Full-text available
Facility location games have been a topic of major interest in economics, operations research and computer science, starting from the seminal work by Hotelling. Spatial facility location models have successfully predicted the outcome of competition in a variety of scenarios. In a typical facility location game, users/customers/voters are mapped to...
Conference Paper
In competitive search settings as the Web, there is an ongoing ranking competition between document authors (publishers) for certain queries. The goal is to have documents highly ranked, and the means is document manipulation applied in response to rankings. Existing retrieval models, and their theoretical underpinnings (e.g., the probability ranki...
Article
We consider an extensive-form game in which players have the option to commit to actions before the game is played. We focus on commitment procedures where players make voluntary irreversible commitments in a prescribed order over the decision nodes. We study whether such commitment procedures may lead to Pareto-efficient outcomes. Our main result...
Article
Full-text available
We introduce an axiomatic approach to group recommendations, in line of previous work on the axiomatic treatment of trust-based recommendation systems, ranking systems, and other foundational work on the axiomatic approach to internet mechanisms in social choice settings. In group recommendations we wish to recommend to a group of agents, consistin...
Article
Agents operating in a multi-agent environment must consider not just their own actions, but also those of the other agents in the system. Artificial social systems are a well known means for coordinating a set of agents, without requiring centralized planning or online negotiation between agents. Artificial social systems enact a social law which r...
Article
Full-text available
Cloud computing has reached significant maturity from a systems perspective, but currently deployed solutions rely on rather basic economics mechanisms that yield suboptimal allocation of the costly hardware resources. In this paper we present Economic Resource Allocation (ERA), a complete framework for scheduling and pricing cloud resources, aimed...
Article
We introduce a synergetic approach incorporating psychological theories and data science in service of predicting human behavior. Our method harnesses psychological theories to extract rigorous features to a data science algorithm. We demonstrate that this approach can be extremely powerful in a fundamental human choice setting. In particular, a ra...
Article
We consider sequential decision making in a setting where regret is measured with respect to a set of stateful reference policies, and feedback is limited to observing the rewards of the actions performed (the so-called bandit setting). If either the reference policies are stateless rather than stateful or the feedback includes the rewards of all a...
Conference Paper
Drawing intuition from a (physical) hydraulic system, we present a novel framework, constructively showing the existence of a strong Nash equilibrium in resource selection games (i.e., asymmetric singleton congestion games) with nonatomic players, the coincidence of strong equilibria and Nash equilibria in such games, and the uniqueness of the cost...
Conference Paper
In the on-line Explore & Exploit [E&E] literature, central to Machine Learning, a central planner is faced with a set of alternatives, each yielding some unknown reward. The planner's goal is to learn the optimal alternative as soon as possible, via experimentation. A typical assumption in this model is that the planner has full control over the ex...
Article
Information delivery in a network of agents is a key issue for large, complex systems that need to do so in a predictable, efficient manner. The delivery of information in such multi-agent systems is typically implemented through routing protocols that determine how information flows through the network. Different routing protocols exist each with...
Conference Paper
Exclusive social groups are ones in which the group members decide whether or not to admit a candidate to the group. Examples of exclusive social groups include academic departments and fraternal organizations. In the present paper we introduce an analytic framework for studying the dynamics of exclusive social groups. In our model, every group mem...
Article
Full-text available
Regular physical activity is known to be beneficial to people suffering from diabetes type 2. Nevertheless, most such people are sedentary. Smartphones create new possibilities for helping people to adhere to their physical activity goals, through continuous monitoring and communication, coupled with personalized feedback. We provided 27 sedentary...
Article
Consider the problem of selecting k items that maximize the value of a monotone submodular set function f, where f can be accessed using value queries. It is well known that polynomially many queries suffice in order to obtain an approximation ratio of $$1 - \frac{1}{e}$$. We consider a variation on this problem in which the value queries are requi...
Article
Full-text available
We study structural properties for information aggregation in settings where self-interested agents take actions sequentially and partially observe each other. Agents optimize their choice of action based on some local information (or `private signal') as well as conclusions they draw from observing actions taken by others. The literature so far ty...
Article
Motivated by applications in clustering and information retrieval, we extend the classical Hotelling setting to deal with multi-facility location duels. In the classical Hotelling setting, customers' locations are taken from the uniform distribution on the $[0,1]$ segment, and there are two facility owners, each needs to decide on the location of h...
Article
Most patients with type 2 diabetes are sedentary despite the clear benefit of regular physical activity, including better glucose control and improvement in quality of life (1). Smartphones could potentially improve patient care by continual communication with patients and sensors that quantify patient behavior (2). Nevertheless, the use of persona...
Article
Robust probabilistic inference is an extension of probabilistic inference, where some of the observations are adversarially corrupted. We model it as a zero-sum game between the adversary, who can select a modification rule, and the predictor, who wants to accurately predict the state of nature. Given a black-box access to a Bayesian inference in t...
Conference Paper
Full-text available
The probability ranking principle (PRP) - ranking documents in response to a query by their relevance probabilities - is the theoretical foundation of most ad hoc document retrieval methods. A key observation that motivates our work is that the PRP does not account for potential post-ranking effects, specifically, changes to documents that result f...
Article
We investigate the effect of limiting the number of reserve prices on the revenue in a probabilistic single item auction. In the model considered, bidders compete for an impression drawn from a known distribution of possible types. The auction mechanism sets up to (Formula presented.) reserve prices, and each impression type is assigned the highest...
Research
Full-text available
Data driven segmentation is the powerhouse behind the success of online advertising. Various underlying challenges for successful segmentation have been studied by the academic community, with one notable exception 􀀀 consumers incentives have been typically ignored. This lacuna is troubling as consumers have much control over the data being collect...
Research
Full-text available
In the on-line Explore and Exploit literature, central to Machine Learning, a central planner is faced with a set of alternatives, each yielding some unknown reward. The planner's goal is to learn the optimal alternative as soon as possible, via experimentation. A typical assumption in this model is that the planner has full control over the experi...