<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Moustafa Alzantot — Writing</title><description>Essays and working notes on LLM post-training, distillation, RL and efficient inference.</description><link>https://alzantot.me/</link><language>en-us</language><item><title>Deep Reinforcement Learning Demystified (Episode 2): Policy Iteration, Value Iteration and Q-learning</title><link>https://medium.com/@m.alzantot/deep-reinforcement-learning-demysitifed-episode-2-policy-iteration-value-iteration-and-q-978f9e89ddaa</link><guid isPermaLink="true">https://medium.com/@m.alzantot/deep-reinforcement-learning-demysitifed-episode-2-policy-iteration-value-iteration-and-q-978f9e89ddaa</guid><description>Markov decision processes, then value iteration and policy iteration for when the environment is known, and Q-learning for when it is not.</description><pubDate>Sun, 09 Jul 2017 00:00:00 GMT</pubDate><category>reinforcement-learning</category><category>q-learning</category></item><item><title>Episode 1: Genetic Algorithm for Reinforcement Learning</title><link>https://medium.com/becoming-human/genetic-algorithm-for-reinforcement-learning-a38a5612c4dc</link><guid isPermaLink="true">https://medium.com/becoming-human/genetic-algorithm-for-reinforcement-learning-a38a5612c4dc</guid><description>Using a genetic algorithm, a gradient-free evolutionary method, to solve the Frozen Lake problem in OpenAI Gym.</description><pubDate>Wed, 07 Jun 2017 00:00:00 GMT</pubDate><category>reinforcement-learning</category><category>genetic-algorithms</category></item><item><title>Deep Reinforcement Learning Demystified (Episode 0)</title><link>https://medium.com/@m.alzantot/deep-reinforcement-learning-demystified-episode-0-2198c05a6124</link><guid isPermaLink="true">https://medium.com/@m.alzantot/deep-reinforcement-learning-demystified-episode-0-2198c05a6124</guid><description>What reinforcement learning is, how to install and run OpenAI Gym, and solving Cart-Pole with a simple random policy search.</description><pubDate>Thu, 27 Apr 2017 00:00:00 GMT</pubDate><category>reinforcement-learning</category><category>openai-gym</category></item><item><title>Tips for Computer Science Junior Students</title><link>https://malzantot.blogspot.com/2014/07/tips-for-computer-science-junior.html</link><guid isPermaLink="true">https://malzantot.blogspot.com/2014/07/tips-for-computer-science-junior.html</guid><description>Advice, written in Arabic, for early-year computer science students aiming for a top tech company or graduate school: strengthen your English, master one programming language, practice, keep learning, and contribute.</description><pubDate>Sat, 19 Jul 2014 00:00:00 GMT</pubDate><category>career</category><category>students</category></item></channel></rss>