Time for another update!
Since the last blog post, we have performed many new experiments with different encoders, decoders, recurrent versions, and flatter hierarchies. Out of these, the best new systems are:
- New encoder - single-byte weights for ESR (exponential sparse reconstruction) encoder using a few re-scaling tricks. Great for Arduino!
- New reinforcement learning decoder that performs conservative Q learning.
The latter in particular is quite nice to have. Previously, we used a type of ACLA algorithm (Actor-Critic Learning Automaton) to perform reinforcement learning. It worked well, but it had some downsides. For instance, the "passive learning" ...
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