Title:
マルチポリシー意思決定を導くための有益な結果を構築するための方法および装置
Document Type and Number:
Japanese Patent JP7262858
Kind Code:
B2
Abstract:
In Multi-Policy Decision-Making (MPDM), many computationally-expensive forward simulations are performed in order to predict the performance of a set of candidate policies. In risk-aware formulations of MPDM, only the worst outcomes affect the decision making process, and efficiently finding these influential outcomes becomes the core challenge. Recently, stochastic gradient optimization algorithms, using a heuristic function, were shown to be significantly superior to random sampling. In this disclosure, it was shown that accurate gradients can be computed—even through a complex forward simulation—using approaches similar to those in dep networks. The proposed approach finds influential outcomes more reliably, and is faster than earlier methods, allowing one to evaluate more policies while simultaneously eliminating the need to design an easily-differentiable heuristic function.
Inventors:
Olson, Edwin
Mehta, Darn Vinh H.
Ferrer, Gonzalo
Mehta, Darn Vinh H.
Ferrer, Gonzalo
Application Number:
JP2022063511A
Publication Date:
April 24, 2023
Filing Date:
April 06, 2022
Export Citation:
Assignee:
THE REGENTS OF THE UNIVERSITY OF MICHIGAN
International Classes:
G05D1/02; G05B13/04; G06N20/00
Domestic Patent References:
| JP2009122779A |
Attorney, Agent or Firm:
Patent Attorney Corporation Asamura Patent Office