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Abstract: I tried to create a model that simulates the spread of a disease that does not have a medicine. I observed the effects of varying parameters, then introduced a concept of deflections which mimic social distancing and social gatherings. I finally made an attempt to evolve these deflections based on a performance metric.
Abstract: Deep Reinforcement Learning is a branch of machine learning techniques that is used to find out the best possible path given a situation. It is an interesting domain of algorithms ranging from basic multi-arm bandit problems to playing complex games like Dota 2. This paper surveys the research work on model-free approaches to deep reinforcement learning like Deep Q Learning, Policy Gradients, Actor-Critic methods and other recent advancements.
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Self-Organizing Feature Maps
MNIST Detection Dataset