コレクション q table reinforcement learning 136015-Q table reinforcement learning
Multi QTable QLearning Abstract Qlearning is a popular reinforcement learning technique for solving shortest path (STP) problem In a maze with multiple subtasks such as collecting treasures and avoiding traps, it has been observed that the Qlearning converges to the optimal path However, the sum of obtained rewards along the path in The Qlearning agent A good way to approach a solution is using the simple Qlearning algorithm, which gives our agent a memory in form of a Qtable In this table of size states x actions we store a value for each stateaction combination Those values estimate the reward we get by taking that action and are called QvaluesQtable learning and deep reinforcement learning are the techniques covered by this paper The two algorithms learn the game of backgammon by using selfplay training In selfplay training, the agent sets up two instances to play against each other After each state transition Deep Reinforcement Learning Playing A Racing Game Byte Tank Q table rei...