Track B
Computational Rationality: Using Reinforcement Learning to Understand and Predict Interactive Behavior
This course introduces computational rationality through the lens of Reinforcement Learning, using it to understand, model, and predict interactive behavior in everyday interaction. The teaching approach is hands-on, utilizing interactive notebooks where participants experiment with algorithms, simulate agents, and explore decision-making dynamics step by step. By the end, participants will gain both a theoretical foundation and practical experience applying computational models to human-computer and human-AI settings.