Analysis and Simulation of Educational Involution Based on Game Theory and Reinforcement Learning

Description

Youth education faces a severe involution which suffers more working and psychological problems and less innovation abilities. To explore some theoretical rules or practical methods improving educational rationality, three work has been done: (1) taking the game theory perspective and applying RL(reinforcement learning) to discuss the evolutionary rules and explore relieving strategies of educational involution; (2) quantifying the “double reduction” policy to construct an improved repeated education game and applying RL at the deadlocked education game stage to explore the optimal strategies; (3) based on the small world network, examining the reliability of the optimal strategy in the group education game.