Uber Technologies, Inc.
TRAINING ADAPTABLE NEURAL NETWORKS BASED ON EVOLVABILITY SEARCH
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Abstract:
Systems and methods are disclosed herein for training neural networks that can be adapted to new inputs, new tasks, new environment, etc. by re-training them efficiently. A parameter vector is initialized for a neural network. Perturbed parameter vectors are determined using the parameter vector. Behavior characteristics are determined for each perturbed parameter vector. The parameter vector is modified by moving it in the parameter vector space in a direction that maximizes a diversity metric. Other neural networks can be trained for new tasks or new environments using the parameter vector of the neural network.
Status:
Application
Type:
Utility
Filling date:
8 Nov 2019
Issue date:
14 May 2020