TRAVEL PLANNING ASSISTANCE SYSTEM, METHOD, AND PROGRAM

A function input means 71 accepts input of a cost function that calculates a cost incurred by an itinerary, the cost function being expressed as a linear sum of terms weighted for each feature that a traveler is expected to intend in the itinerary. A learning means 72 learns the cost function by inverse reinforcement learning using training data that includes scheduled information indicating travel planning of the traveler, attribute information indicating an attribute of the traveler, and actual information indicating an actual travel result of the traveler. A data extraction means 73 extracts the training data whose specified attribute matches the attribute information. Then, the learning means 72 learns the cost function according to the attributes by inverse reinforcement learning using the extracted training data.