🎲 #2: People learned gains and losses equally well, but their risk preferences differed: more risk in gains, more caution in losses. In lotteries, this pattern is reversed, revealing a strong gap between experience and description, and in contrast with the Prospect Theory.

📊 #1: Complete feedback increased risk-taking more than it improved EV maximization. It helped only when the risky option was optimal, indicating that richer feedback shifts risk attitude rather than accuracy.

🧩 We focused on two key factors:
Feedback richness: Do people see only the outcome of their choice, or also what would have happened if they chose differently?
Valence: Are they dealing with gains or with losses?

Here are the two main results:

🧠Our new preprint is out on PsyArXiv!

We study how getting more feedback (seeing what you could have earned) and facing gains vs losses change the way people choose between risky and safe options.
🖇️Link: doi.org/10.31234/osf...

It's a thread🧶:

I'm feeling very glad & grateful these days to be part of neuroeconomics summer school in Fontainebleau! 👾

I recently took part in an amazing experience at the “Solve for Healthcare & Life Sciences with Gemma” hackathon, organized by Google Paris!
Our team worked on triage in emergency rooms, improving communication, prioritization and decision-making in critical circumstances.

I'll be presenting two posters at #RLDM2025 in Dublin🇮🇪 – June 11, Poster Session 1:

🌀 Poster #19: How selective attention benefits and hinders learning in complex environments.

🏞️ Poster #18: NorMARL - a framework for sustaining shared resources through norm internalization.

Paris Magnolias
at the Jardin du Palais Royal ⛅

🌍 Excited to share that our paper has been accepted for an oral presentation at the International Conference on Complex Systems (FRCCS) 2025 in Bordeaux!

We demonstrate how norm internalization and learning rate influence sustainability, via a cognitively grounded multi-agent RL framework.

🎉 I'm excited to share that 2 of our papers got accepted to #RLDM2025!

📄 NORMARL: A multi-agent RL framework for adaptive social norms & sustainability.
📄 Selective Attention: When attention helps vs. hinders learning under uncertainty.

Grateful to my amazing co-authors! *-*

After a couple of years, why are we still very far from the dream world of blockchains and smart contracts?

The interindividual exposure