Posts related to passion projects of mine – from competitive programming to deep learning applications. Most of these will be open sourced with a corresponding GitHub project and/or Google Colab notebooks.
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(Paper Review) Motivational Profiling of League of Legends Players
This is a review of the journal article “Motivational Profiling of League of Legends Players” by Brühlmann et al., 2020 [1]. Overview The authors use an Organismic Integration Theory (OIT) based questionnaire called the User Motivation Inventory (UMI)[2], which is designed to measure player motivational regulations. After gathering 750 participants from the League of Legends…
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Monte Carlo Tree Search (Part 2): A Complete Explanation with Code
In the last post we discussed the problem of acting optimally in an episodic environment by estimating the value of a state. Monte Carlo Tree Search (MCTS) naturally fits the problem by incorporating intelligent exploration into decision-time multi-step planning. Give that post a read if you haven’t checked it out yet, but it isn’t necessary…
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Monte Carlo Tree Search (Part 1): Introduction to MDPs
Following on from the idea of learning to make an optimal single decision, we can expand this to making multiple sequential decisions in an optimal way. To do this we’ll be exploring Monte Carlo Tree Search (MCTS); an algorithm that combines ideas from traditional tree search algorithms, and reinforcement learning (RL). Today we’re going to…