An efficient exploration method for reinforcement learning. The method comprises the following steps: 1) pre-training a counting estimate function; and 2) carrying out efficient exploration of reinforcement learning by using the pre-trained counting estimate function. The method mainly targets the problem of balancing exploration and utilization in reinforcement learning. In a continuous space task, the frequency of occurrence of states encountered by an intelligent body is estimated by means of the pre-trained counting estimate function, rewards are calculated using the frequency of occurrence of the states, and the intelligent body is guided by means of the rewards to explore the states which are encountered less so that efficient exploration is achieved. A reward signal is processed by means of using an independent exploration strategy, so that the influence of the reward signal on an action strategy of the intelligent body is prevented, and the exploration process is more stable.
EFFICIENT EXPLORATION METHOD FOR REINFORCEMENT LEARNING