The letter detailed a project known internally as Q* (Pronounced Q-Star) or Q-Learning. This project was ... the highest number is the most optimal solution found (so far or at a given time) by that ...

In order to elaborate on this concept and demonstrate the fundamentals of reinforcement learning, two well-known algorithms ... Q-value since it has learned its policy based on the optimum policy. Let ...

Example: Agent wants to go to the east ... Two arrows basically mean that for the both actions Q(s,a) value was the same and equal to the maximum. The algorithm converges after 34 iterations. Here we ...

A hybrid intelligent algorithm integrating Q-learning is innovatively designed ... The structure of the solution is shown in Figure 3, taking Ship 1 as an example. Ship 1 is the third in the berthing ...

For example, in the CliffWorld map, Q Learning finds the optimal solution near the obstacles, while SARSA tends to take more steps away from the obstacles, making it a more conservative algorithm.

which improves standard Q-learning algorithm so that the proposed algorithm seeks for the optimal solution ensuring that the safety premise is satisfied. During the process of finding the solution in ...

Exploration avoids the partial optimal solution but too much exploration will reduce the performance of the Q -learning algorithm. How to avoid the partial optimal solution and find the global optimum ...