Deep reinforcement learning can be applied to solve the taxi drop game by training a neural network to learn the optimal policy for the taxi agent. The network takes the current state of the game as input and outputs the best action to take. Through trial and error, the agent learns to maximize its cumulative rewards.
SalilBhatnagarDE/DRL_taxi_game
Deep reinforcement learning can be applied to solve the taxi drop game by training a neural network to learn the optimal policy for the taxi agent. The network takes the current state of the game as input and outputs the best action to take. Through trial and error, the agent learns to maximize its cumulative rewards.
Apache-2.0