Compute Model of Operant Conditioning Based on Probabilistic Automata

This paper constructs a stochastic learning automaton that can respond the operant conditioning behavior based on probabilistic automata,which is used for simulating skinner-pigeon experiment. The stochastic learning automaton is a kind of intelligent unit which can accomplish adaptive decision under unknown environment,and so it can let an agent to adapt its actions to gain maximally from the environment while only being rewarded for correct performance. A stochastic learning automation model is established to be applied to skinner-pigeon experiment of the peck button task. The pigeon learns this task in stages. In simulation,the model also acquires the task in a similar manner. The stochastic learning automaton has outstanding superiority in dealing with the problem of lack of prior knowledge,which lays a theoretical foundation for copying the behaviors of people and animal by robot learning.