INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM

An information processing device includes a definer, a determiner, and a reinforcement learner. The definer is configured to associate a node and an edge with attributes and to define a convolution function associated with a model representing data of a graph structure representing a system structure on the basis of data regarding the graph structure. The evaluator is configured to input a state of the system into the model. The evaluator is configured to obtain, for each time step, a policy function as a probability distribution of a structural change and a state value function for reinforcement learning for a system of one or more structurally changed models which have been changed with assumable structural changes from the model for each time step. The evaluator is configured to evaluate the structural changes in the system on the basis of the policy function. The reinforcement learner is configured to perform reinforcement learning by using a reward value as a cost generated when the structural change is applied to the system, the state value function, and the model, to optimize the structural change in the system.