Fujitsu Corporation

Vishal Sharma

Eiji Kitagawa

Takuro Ikeda

Taizo Anan

An action selection learning device includes a memory; and a processor coupled to the memory and configured to generate a reference model that is a set of model parameter vectors that indicate an influence level of each factor that influences selection of an action alternative, calculate a selection probability for each action alternative, for each of the model parameter vectors, calculate a model parameter vector for each user using a subset of model parameter vectors extracted from the reference model, based on the selection probability for each action alternative and a selection history of the action alternative by each user, generate the action alternatives based on the model parameter vector for each user, and transmit the generated action alternatives to a terminal device.

Action selection learning device, action selection learning method, and storage medium

A congestion management apparatus includes a memory configured to store, on a per-action-option basis, upper limits on numbers of users allowed to be guided to action options, and a processor coupled to the memory and configured to: generate the action options by time slot for a user; calculate for each of the generated action options, choice probabilities of the action options with respect to the user, and store the calculated choice probabilities in the memory; and calculate for each of the action options, estimated numbers of previous users assumed to have selected the action options, based on choice probabilities of each of the action options with respect to the previous users, the choice probabilities being obtained from the memory, wherein the processor is configured to extract, based on the upper limits and the estimated numbers for the action options, action options to be presented to the user.

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Singapore, Singapore

Vishal Sharma