Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting — mentioned by ben_w

Tue, 11 Dec 2018 16:25:07 GMT

> We're not deep learning systems. So reasoning by analogy there isn't correct. That’s why I’m asking which definition you’re using. It’s broad enough that some models are biologically plausible even though there is criticism that many others are not: https://arxiv.org/abs/1502.04156 > Deep learning systems, are examples of supervised learning. Once trained, they cannot adapt to new input. You have to retrain to accommodate new features that you want to capture. Supervised, unsupervised, and reinforcement; and there is work on both incremental learning (https://arxiv.org/abs/1712.02719) and…

Paper and discussion history. A mention is not an endorsement.

Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting · HackerPapers discussions

Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting — mentioned by ben_w