Research
Research on strategic reasoning, learning, and decisions from experience.
How do people learn to reason strategically, and does what they learn persist and transfer? My work tackles questions like these with laboratory experiments, process-tracing and eye-tracking, and computational models, and now extends them to interaction with artificial agents.
Full list and citations on Google Scholar · Download CV
Research agenda
My research agenda is organized in two connected streams, both grounded in the economics of bounded rationality and strategic interaction.
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.
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.
Papers under review
Excessive and conspicuous consumption: Evidence from the United Arab Emirates
Nikiforakis, N., Bernardini, F., Cappellini, C., Janas, M., Marchiori, D., Lozano, L., Siegenthaler, S., & Attar, R. (Revise and resubmit). Behavioural Public Policy.
Heuristic play through equilibrium-consistent feedback
Di Guida, S., Marchiori, D., Mayaux, D., & Polonio, L. (Under review). Theory and Decision.
Work in progress
Learning, persistence, and transfer of strategic sophistication
Marchiori, D., Di Guida, S., & Polonio, L. (In progress). Presented at IMESS 2026, NYU Paris.
Strategic sophistication in human–AI interaction
Marchiori, D. (In progress). Multi-study project (see research agenda).
Journal articles
Testing the convergent validity, domain generality, and temporal stability of selected measures of people’s tendency to explore
Anvari, F., Billinger, S., Analytis, P. P., Franco, V. R., & Marchiori, D. (2024). Nature Communications, 15, 7721.
K-Alpha Calculator – Krippendorff’s Alpha Calculator: A user-friendly tool for computing Krippendorff’s alpha inter-rater reliability coefficient
Marzi, G., Balzano, M., & Marchiori, D. (2024). MethodsX, 102545.
Percent framing attenuates the magnitude effect in a preference-matching task of intertemporal choice
Anvari, F., Verdeș, D. D., & Marchiori, D. (2022). PLoS ONE, 17(1).
Priming exploration across domains: Does search in a spatial environment influence search in a cognitive environment?
Anvari, F., & Marchiori, D. (2021). Royal Society Open Science, 8, 201944.
Plasticity of strategic sophistication in interactive decision-making
Marchiori, D., Di Guida, S., & Polonio, L. (2021). Journal of Economic Theory, 196, 105291.
Hierarchical decision-making produces persistent differences in learning performance
Knudsen, T., Marchiori, D., & Warglien, M. (2018). Scientific Reports, 8, 15782.
Cross-cultural differences in decisions from experience: Evidence from Denmark, Israel, and Taiwan
Di Guida, S., Erev, I., & Marchiori, D. (2015). Journal of Economic Psychology, 49, 47–58.
Toward a general theoretical framework for judgment and decision-making
Marchiori, D., & Aharon, I. (2015). Frontiers in Psychology, 6, 159.
Noisy retrieval models of over- and undersensitivity to rare events
Marchiori, D., Di Guida, S., & Erev, I. (2015). Decision, 2, 82–106.
On loss aversion, level-1 reasoning, and betting
Erev, I., Gilat-Yihyie, S., Marchiori, D., & Sonsino, D. (2015). International Journal of Game Theory, 44, 113–133.
Decisions among defaults and the effect of the option to do nothing
Di Guida, S., Marchiori, D., & Erev, I. (2012). Economics Letters, 117, 790–793.
Physiological plausibility and boundary conditions of theories of risk sensitivity
Marchiori, D., & Elqayam, S. (2012). Frontiers in Psychology, 3, 33.
Neural network models of learning and categorization in multigame experiments
Marchiori, D., & Warglien, M. (2011). Frontiers in Neuroscience, 5, 139.
Predicting human interactive learning by regret-driven neural networks
Marchiori, D., & Warglien, M. (2008). Science, 319, 1111–1113.
Book chapters
Pack light if on the move: Exploitation and exploration in a dynamic environment
LiCalzi, M., & Marchiori, D. (2014). Artificial Economics and Self Organization, S. Leitner & F. Wall (Eds.), pp. 205–216. Springer.
Constructing shared interpretations in a team of intelligent agents: The effects of communication intensity and structure
Marchiori, D., & Warglien, M. (2005). Agent-Based Simulation: From Modeling Methodologies to Real-World Applications, T. Terano et al. (Eds.), pp. 58–71. Springer Tokyo.
Recent presentations
Oct 2026
Behavioural Policy for Family workshop
The Policy Institute, King’s College London. Participant.
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.
Selected earlier talks
Jun 2019
Plasticity of human strategic sophistication in interactive decision-making
NeuroPsychoEconomics Conference, LUISS University, Rome.
Apr 2019
Frontiers of Organization Studies workshop
Invited participant. Center for Advanced Study in the Behavioral Sciences (CASBS), Stanford University.
Jan 2019
Reciprocal Bounded Rationality and the Complexity Foundations of Strategy Science
Invited participant. Max Planck Institute for Mathematics in the Sciences, Leipzig.
May 2018
Distributed hierarchical decision processes produce persistent differences in learning performance
NeuroPsychoEconomics Conference, University of Zürich.
Jun 2017
Thou shalt not steal!
Invited participant. Learning by Stealing Workshop, MIT Sloan School of Management.
Jan 2017
Microfoundations of Expectations workshop
Invited participant. Max Planck Institute for Mathematics in the Sciences, Leipzig.
Sep 2015
Attention allocation and learning in hierarchical organizations
Invited speaker. Experimental Organization Science (EOS) Workshop, Frankfurt School of Finance & Management.
May 2015
Multi-level learning in hierarchical organizations
Invited speaker. TOM Conference, Ca’ Foscari University of Venice.
Nov 2014
Multi-level learning in hierarchical organizations
Invited speaker. COPE Workshop on Change, Organizational Plasticity, and Evolution, Universitat Pompeu Fabra, Barcelona.
Jan 2012
Over- and under-sensitivity to rare events: Distinct processes or noisy retrievers?
Invited speaker. Erasmus–Technion Workshop on Decisions and Predictions, Ein Bokek, Israel; invited seminar, Academia Sinica, Taipei.
Grants & awards
2017
Independent Research Fund Denmark
Project LEADER – Learning in Dynamic Environments (Principal Investigator), DKK 3,330,327 (approx. EUR 447,000).
2016
Brødrene Hartmanns Fond
Project on reducing underweighting of rare events, with Daniel Newark, DKK 30,000.
2012
Academic Research Award
For outstanding research achievement, College of Social Sciences, National Chengchi University.
2012
National Science Council of Taiwan
One-year research grant (Principal Investigator), NTD 555,000.
2010
Best PhD Graduates’ Award
AY 2009/2010, University of Trento.
2010
Lady Davis Postdoctoral Fellowship
Technion – Israel Institute of Technology.