Learning Machine Learning with Aston

STEM: I was absent Monday and Tuesday of this week as I was out sick so this journal is mainly going to be about my spring break and what I've done since the technical journal. For the technical stuff, I have begun to move towards a middle job area of helping around both with the q learning with Robert and Connie and our game code with Puja, Edmond, and Will. I helped with the debugging of the game with an example of us fixing the game crash when wrong inputs are given. Other work includes trying to develop the reward aspect of the Q learning algorithm. Because Will and Edmond are out for a robotics competition, I see myself working with Puja on the code more this week. Spring Break: Over spring break, I went to Italy with my family. We stopped in Rome, Florence, and Milan over the week! Rome was our first stop and we went to see the Colosseum and the Roman Forum which were very historical and impressive. We also visited the Pantheon and I was amazed by the large d...

Tic Tac Toe Data: We first planned on spending this two weeks looking into datasets for tic tac toe and processing it as a pre-trial for our dots and boxes. What we found and did though, I though was far more insightful. Initially, I was looking around for datasets and found from UVA a dataset for tic tac toe intermediate game states. We thought this could be something as the UCI dataset that we had first come across only gave endgame states. An image of the UVA dataset is posted below. Discussing with Mr. Lee, though, we could not decipher what the non-zero/one numbers represented and decided to move on looking, a sort of dead end. We inferred that -1 and 1 were X and O while 0 was blank. We would eventually later find another way to gather datasets (see Tic Tac Toe Q Learning below). Part of Tic Tac Toe intermediate game states data Tic Tac Toe Monte Carlo: While we had been looking into datasets, it turns out that Will was experimenting with the Monte Carlo search tre...

Genetic Algorithm: After briefly looking into SARSA learning, I decided to switch and explore genetic algorithms after receiving a research paper Connie sent me. In this paper, researchers who were teaching an AI to play dots and boxes explained that they had used a genetic algorithm to create their neural network. As a result, I looked into genetic algorithms and was quite excited. This was because I could really connect with the algorithm as it was based on biology that I have studied. The close comparison made this research more tangible to me and I felt that I could relate more to it. The algorithm is explained in my Concept Map video below but it is basically an algorithm that simulates natural selection to choose the most "fit" neural network.  Caltech Visit: We visited Caltech on Thursday though we were short on people. This was because Edmond and Will were at a Robotics competition and Puja was stuck in Chemistry. Nevertheless, Robert, Connie, and I talked w...