Invention Grant
- Patent Title: Training neural networks using evolution based strategies and novelty search
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Application No.: US16220533Application Date: 2018-12-14
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Publication No.: US11068787B2Publication Date: 2021-07-20
- Inventor: Edoardo Conti , Vashisht Madhavan , Jeffrey Michael Clune , Felipe Petroski Such , Joel Anthony Lehman , Kenneth Owen Stanley
- Applicant: Uber Technologies, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Uber Technologies, Inc.
- Current Assignee: Uber Technologies, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Fenwick & West LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06N5/04

Abstract:
Systems and methods are disclosed herein for selecting a parameter vector from a set of parameter vectors for a neural network and generating a plurality of copies of the parameter vector. The systems and methods generate a plurality of modified parameter vectors by perturbing each copy of the parameter vector with a different perturbation seed, and determine, for each respective modified parameter vector, a respective measure of novelty. The systems and methods determine an optimal new parameter vector based on each respective measure of novelty for each respective one of the plurality of modified parameter vectors, and determine behavior characteristics of the new parameter vector. The systems and methods store the behavior characteristics of the new parameter vector in an archive.
Public/Granted literature
- US20190188571A1 TRAINING NEURAL NETWORKS USING EVOLUTION BASED STRATEGIES AND NOVELTY SEARCH Public/Granted day:2019-06-20
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