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 ...

It was tested whether the ,,strong'' agent is able to compete with the long-known Alpha-Beta pruning algorithm in the Connect 4 game. Using reinforcement learning methods and neural networks, an agent ...

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 ...

The number (quantity) and the accuracy (quality) of solutions are equally important in solving multimodal optimization problems (MMOP). This paper proposes a Q-learning-based brainstorming ...