Modeling Social Learning Using Dyna-Q and Ant Colony Optimization
Renato Zimmermann · PARETO Undergraduate Journal of New Economists · 2023
This paper introduces a novel way of modeling social learning in macroeconomics using techniques from model-based reinforcement learning and ant colony optimization. The work extends previous works in bounded rationality and social learning by providing tools to complement previously-distinct models in adaptive learning. We test these new techniques using simulations of job search and consumption. Results demonstrate that models fit using the proposed techniques can learn core economic behaviours given no information about the environment, but do not fully fit reward functions in line with rational expectations theory.