Behavioral and experimental economist at NYU Abu Dhabi

How do people learn to think strategically?

I’m Davide Marchiori. I study how people learn, adapt and develop strategic reasoning through experience, and what changes when the other side of the table is an artificial agent. My tools are lab experiments, eye-tracking and process-tracing, and computational models.

Published in Science, Nature Communications, Journal of Economic Theory, Journal of Economic Psychology and Scientific Reports.

Play one round

Demo: a level-2 scanpath

You choose a row; the other player chooses a column. In each cell your payoff is the bold number, theirs is the grey one. Read the numbers with your mouse, then click a row.

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The circles show where a level-2 player looks: the other player’s payoffs first, then their own payoffs in the column they expect.

  • Behavioral and experimental economics
  • Strategic sophistication and bounded rationality
  • Human–AI interaction in strategic settings
  • Learning and decisions from experience
  • Process-tracing and eye-tracking methods
  • Computational models of cognition
  • Behavioral public policy

Research agenda

Full agenda and papers

Stream 1

Dynamics and transfer of strategic sophistication

Building on my eye-tracking work on the plasticity of strategic sophistication (Journal of Economic Theory, 2021), this stream studies how strategic reasoning is learned, how persistent it is, and whether it transfers across games and environments.

  • Learning, persistence, and transfer of strategic sophistication

    Presented at IMESS 2026, NYU Paris.

  • Heuristic play through equilibrium-consistent feedback

    Under review, Theory and Decision.

Stream 2

Strategic decision-making with artificial agents

A natural extension of the first stream to settings where the counterpart is an algorithm.

  • Beliefs about AI reasoning

    How people attribute depth of reasoning to AI counterparts in normal-form games, using process-tracing to separate beliefs about the opponent from one’s own reasoning depth.

  • Learning from AI counterparts

    Whether repeated interaction with AI agents of controlled sophistication changes human strategic reasoning, and whether those changes transfer to games against humans.

  • Negotiation and delegation

    Bargaining with large-language-model agents and the decision to delegate strategic choices to AI, with implications for institutional and market design.

Career

  1. 2025–now

    Senior Research Scientist

    Center for Behavioral Institutional Design (C-BID), NYU Abu Dhabi

  2. 2024–2025

    Laboratory Technologist, Behavioral Research Support

    IMT School for Advanced Studies Lucca, Italy

  3. 2013–2023

    Associate and Assistant Professor

    University of Southern Denmark

  4. 2010–2013

    Faculty and research positions

    Ca’ Foscari Venice, NCCU Taipei, Technion

Full background

Recently

  1. Oct 2026

    Behavioural Policy for Family workshop

    The Policy Institute, King’s College London. Participant.

  2. Aug 2026

    Learning, Persistence, and Transfer of Strategic Sophistication

    4th International Meeting in Experimental Social Science (IMESS), joint workshop with NYU Abu Dhabi C-BID and NYU CESS, NYU Paris.

  3. Under review

    Excessive and conspicuous consumption: Evidence from the United Arab Emirates

    Revise and resubmit, Behavioural Public Policy.