Reinforcement learning in Agent-based macroeconomic model
|Autor:||Mgr. Bořivoj Vlk|
|Rok:||2018 - letní|
|Vedoucí:|| PhDr. Ing. Jiří Skuhrovec PhD.
|Typ práce:|| Diplomová
|Abstrakt:||Utilizing game theory, learning automata and reinforcement learning concepts, thesis
presents a computational model (simulation) based on general equilibrium theory
and classical monetary model.
Model is based on interacting Constructively Rational agents. Constructive Rationality
has been introduced in current literature as machine learning based concept
that allows relaxing assumptions on modeled economic agents information and expectations.
Model experiences periodical endogenous crises (Fall in both production and consumption
accompanied with rise in unemployment rate). Crises are caused by firms
and households adopting to a change in price and wage levels. Price and wage level
adjustments are necessary for the goods and labor market to clear in the presence
of technological growth.
Finally, model has good theoretical background and large potential for further development.
Also, general properties of games of learning entities are examined, with
special focus on sudden changes (shocks) in the game and behavior of game’s players,
during recovery from which rigidities can emerge.