Operant conditioning automata model and a bionic autonomous learning process

This paper presents an operant conditioning automata model (hereinafter referred to ¿OCM¿), and designs a bionic autonomous learning method which can be used to describe and simulate a bionic autonomous learning process. The model can be considered as an active learning permitting to select a better action according to psychology behavior propensity, and the aim is to learn to find the optimal action finally. During the learning process, the system selects an action randomly according to the probability distribution of action selection, which is updated by the behavior propensity from the environment. We apply our model on skinner-pigeon experiment. In simulation, we confirmed that this model could successfully simulate operant conditioning.