Simple Reinforcement learning example, based on the Q-function.
- Rules: The agent (yellow box) has to reach one of the goals to end the game (green or red cell).
- Rewards: Each step gives a negative reward of -0.04. The red cell gives a negative reward of -1. The green one gives a positive reward of +1.
- States: Each cell is a state the agent can be.
- Actions: There are only 4 actions. Up, Down, Right, Left.
The little triangles represent the values of the Q function for each state and each action. Green is positive and red is negative.
Three different agents are currently implemented.
Run:
python QLearner.py
Run:
python SarsaLearner.py
Run:
python SarsaLambdaLearner.py