Epsilon-Greedy Exploration
Example:
In a simple grid world, an agent can move up, down, left, or right. The agent receives a reward of +1 for reaching the goal state. We want to learn the value function using epsilon-greedy exploration.
Constraints:
epsilon = 0.1, gamma = 0.9
Implement epsilon-greedy exploration to select actions.
Test Cases
Test Case 1
Input:
[[0.5, 0.3], [0.2, 0.1]]Expected:
0Test Case 2
Input:
[[0.1, 0.2], [0.3, 0.4]]Expected:
1+ 3 hidden test cases