Chanattan R. Sok

CS Student Researcher

I am a Master student at Sorbonne University and École Normale Supérieure (ENS) de Rennes in Computer Science, France, focusing on multi-agent systems and decision. My research integrates decision-making (aid), societal challenges, and artificial intelligence.

I address interdisciplinary challenges with multi-agent systems, socio-economics (e.g., mechanism design, fairness, recommendation systems), learning, and game theory. My recent interests focus on auctions, incentives and mechanisms with societal impact.

Agent-Based Modelling Reinforcement Learning Decision-making Mechanism Design Game Theory

Publications & Preprints

Currently working on two conference papers on fairness in railway networks, and in multi-criteria collective decision-making.

Towards an Energy Twin: Simulating Global Warming Potential in Hamburg's Building Stock

Chanattan Sok, Rico Herzog, Arnaud Grignard.
In Review — Special Issue Urban Digital Twins
Simulation et résolution de conflits spatiaux entre piétons fondée sur la théorie du choix social

JFSMA 2025 — Chanattan Sok, Olivier Simonin. · English version (ECAI submission)
JFSMA 2025
WebAssembly Serverless Join: A Study of its Application

SSDBM 2024 — Chanattan Sok, Laurent d'Orazio, Reyyan Tekin, Dimitri Tombroff.
SSDBM 2024

Projects

CNM

Conflict Negotiation Model — pedestrian simulation platform using social choice theory. Published at JFSMA 2025.

MAS Python / Mesa Simulation

tweakable_model

Generic n-choice negotiation model inspired from Putnam's two-level game theory. Batch experiments with genetic algorithms.

MAS Python / Mesa

IsomEdit

Isometric map editor built in Java, Swing. A personal tool for 2.5D game design and content creation workflows.

Java

Thoth

Stock investment simulator with AI assistance. Simulated press events with randomised market impact, Brownian motion stock prices, and Thoth — an ARIMA-based AI agent that analyses price curves and news to predict trends over a few months. Human–AI feedback loop for improved synergy, with portfolio and ROI tracking.

Python ARIMA Finance

train_mystery

Collaborative mystery game set aboard a train, written in Rust. A fun game-jam-style project with colleagues made under 23 hours. Code, story and design were all made collaboratively : I focused on prototyping, game design, narrative and art making.

Rust

satellite_coordination

Satellite coordination via auction-based mechanisms for collective decision-making, and distributed constraint optimisation (SDCOP — Sequential Distributed Constraint Optimisation Problem). Project based from Gauthier Picard's article at AAMAS 2022 (https://arxiv.org/pdf/2106.03548), working for ONERA/DTIS, and Toulouse University.

MAS Auctions Python DCOP