More random posts on ML: https://github.com/chetan51/linguist?tab=readme-ov-file https://github.com/chetan51/linguist https://github.com/as3445/NuPIC-Stock-Prediction https://github.com/ywcui1990/TrafficPrediction https://github.com/youngminpark2559/connections_between_HTM_video_and_NuPIC_code ==== https://www.cell.com/neuron/pdf/S0896-6273(17)30509-3.pdf Reinforcement Learning Alongside its important role in the development of deep learning, neuroscience was also instrumental in erecting a second pillar of contemporary AI, stimulating the emergence of the field of reinforcement learning (RL). RL methods address the problem of how to maximize future reward by mapping states in the environment to actions and are among the most widely used tools in AI research (Sutton and Barto, 1998). Although it is not widely appreciated among AI researchers, RL methods were