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Tobiwan663 t1_iro5hgz wrote

Hello Dear ML community,

I am an machine learning student looking for an interesting research topic, more specifically I am interested in modeling algorithmic thinking through neural networks. Of course Reinforcement Learning methods come to mind but they mostly make use of tree search and some value/policy function(s) modeled by neural networks. For me such an RL setting does not sound very promising when it comes to General AI because the only known general intelligent system (brain) does not appear to use tree search explicitly but rather as an product of its general intelligence emerging from neural activity. Do you know of any research sub-areas which try to understand these questions?

Appreciate any hints!

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Dimitri_3gg t1_iropv0e wrote

Computational neuroscience for machine learning - the study of the brain and its computation to improve the currently naive simplification of ANNs. Deep learning is miles behind the human brain in aspects such as learning and actual deep understanding.

Genetic programming for deep learning- fun methodology of guided randomization to learn neural networks.

Predictive coding - Rao & Ballard. A more advanced form of the MLP which forward propagates errors between predictions and observations rather than input. Spratling 2017 is a good review, but the Rao and Ballard 1999 is fundamental.

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