A cliff walking grid-world example is used to compare SARSA and Q-learning, to highlight the differences between on-policy (SARSA) and off-policy (Q-learning) methods. This is a standard undiscounted, episodic task with start and end goal states, and with permitted movements in four directions (north, west, east and south). The reward of -1 is used for all transitions except the regions marked The Cliff, stepping on this region will penalize the agent with reward of -100 and sends the agent instantly back to the start position.
The following snippets of code have taken inspiration ...
