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.

http://youtu.be/tiTR8F41_v0

Three different agents are currently implemented.

Run:

python QLearner.py

Run:

python SarsaLearner.py

Run:

python SarsaLambdaLearner.py