סמינרים
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(Neuro)Cognitive Constraints in Decision-Making: From Consumer Behavior to Strategic Choice
ABSTRACT The human mind has finite computational cognitive capacity. First, I will briefly discuss how specific neurobiologically defined cognitive limitations can yield improved behavioral models of inconsistencies and context-effects in individual decision-making and in consumer choice. Then, I will devote the bulk of the talk to a similar analysis of strategic choice. Classical game theory… Continue Reading (Neuro)Cognitive Constraints in Decision-Making: From Consumer Behavior to Strategic Choice
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Computational and Statistical Limits in Modern Machine Learning – Job Talk
Abstract: Modern machine learning systems operate in regimes that challenge classical learning-theoretic assumptions. Models are highly overparameterized, trained with simple optimization algorithms, and rely critically on how data is collected and curated. Understanding the limits of learning in these settings requires revisiting both the computational and statistical foundations of learning theory. A central question in learning… Continue Reading Computational and Statistical Limits in Modern Machine Learning – Job Talk
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Comparison of Oracles
Abstract: We analyze incomplete-information games where an oracle publicly shares information with players. One oracle dominates another if, in every game, it can match the set of equilibrium outcomes induced by the latter. Distinct characterizations are provided for deterministic and stochastic signaling functions, based on information matching, partition refinements, and common knowledge components. This study… Continue Reading Comparison of Oracles
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The Agent Perspective In LLM-Based Strategic Information Retrieval Ecosystems
Abstract: Information retrieval ecosystems are strategic environments in which publishers, mediators, advertisers, and users interact under mechanisms that allocate visibility and revenue. The integration of large language models (LLMs) into search and question answering systems fundamentally reshapes these dynamics, altering ranking incentives and long-term corpus evolution. My dissertation develops a unified strategic perspective on LLM-based… Continue Reading The Agent Perspective In LLM-Based Strategic Information Retrieval Ecosystems
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Creating closed lists for proportional elections: Mechanism design for inner-coalition elections
Abstract: During parliamentary elections, it is common in many countries to use the D'Hondt method known to promote coalitions with closed lists. It follows that a game exists between parties of the same coalition to determine the list that they submit to represent the coalition in the election. It is common for list makers… Continue Reading Creating closed lists for proportional elections: Mechanism design for inner-coalition elections
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An Epistemic Model with Boundedly-Rational Players
Abstract: I propose a general and simple framework for studying epistemic foundations of noncooperative solution concepts: A player faces a strategic situation described by an epistemic picture, which is a set of statements written in a formal language. The player takes his epistemic picture as given; constructs a state space and a set of acts;… Continue Reading An Epistemic Model with Boundedly-Rational Players
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Motivated Misspecification
Abstract: I propose a model of expectation management to investigate how the type of misperception is determined in a principal-agent framework. In my model, the principal controls the agent’s expectation of a project's potential, and the agent exerts effort over time. An unrealistically high expectation stimulates effort in the short run but potentially backfires and… Continue Reading Motivated Misspecification
