I'm building an RL agent using SARSA and Q-Learning for testing its capabilities.
The environment is a 10x10 grid, where it gets a reward of 1 if he reaches the goal while he takes -1 every time he takes a step out of the grid. So, it can freely move out and every time it takes a step outside of the grid it gets -1.
After tuning the main parameters
- alpha_val: 0.25
- discount: 0.99
- episode_length: 50
- eps_val: 0.5
I get the following plot for 10000 episodes (The plot is sampled every 100 episodes):
But when I look at the plots online I see usually plots like this one:
Since I'm new at RL, I'm asking some comments about my outcome or any type of suggestion if anyone of you think that I'm doing something wrong.