Compare Sarsa algorithm with Qlearning algorithm.
For detail comparison，go to https://blog.csdn.net/qq_39004117/article/details/81705845 (in Chinese)
The basic environment is described as follows:
The agent is in a maze. Given the entrance and exit of the maze, he should find the exit without falling into the snare. If he arrives at the destination, then the game is over. But if he goes into the snare, then he will get -100 reward, and then restart from the entrance. For each step, he will get -1 reward.
So, the state of the agent is his current position, specifically (x, y).
The action of the agent is the moving direction. The action space is discrete. The agent can go toward four direactions each timestep, specifically, left, right, up and down.
the map of the game shown as follows:
Run this algorithm, you need to install the following python lib:
- matplotlib
- numpy