Research Article
Unbiased Model-Agnostic Metalearning Algorithm for Learning Target-Driven Visual Navigation Policy
Algorithm 1
Local Model: metatraining phase.
| | Require: and : step hyperparameters | | (1) | Randomly initialize | | (2) | | | (3) | whiledo | | (4) | Sample batch of tasks | | (5) | for all do | | (6) | Collect trajectories using in | | (7) | Evaluate using equation (2) | | (8) | Compute adapted parameters with gradient descent: | | (9) | Collect trajectories using in | | (10) | end for | | (11) | Update using equation (2) | | (12) | end while |
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