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General Game Playing As A Bandit-Arms Problem: A Multiagent Monte-Carlo Solution Exploiting Nash Equilibria, Brandon Mathewe Banda
General Game Playing As A Bandit-Arms Problem: A Multiagent Monte-Carlo Solution Exploiting Nash Equilibria, Brandon Mathewe Banda
Honors Papers
This project approaches general game playing in a unique way by combining popular methods of stochastic tree searching with a Multiagent system and a unique algorithm that I call the Wise Explorer algorithm. The goal of the system is to explore the worst possible branches of the game first to rule them out, followed by an in-depth search on the most promising branches. The system constantly refers to the data it collects during its extensive search, and it outputs a strategic move for any given state of a game. In essence, if you’re ever in a bind during a game …
Can Machine Learning On Economic Data Better Forecast The Unemployment Rate?, Aaron S. Kreiner
Can Machine Learning On Economic Data Better Forecast The Unemployment Rate?, Aaron S. Kreiner
Honors Papers
This paper examines different machine learning methods to project the U.S. unemployment rate one year ahead. The forecasts include a naive forecast equal to the current unemployment plus the change of unemployment over the last year, along with forecasts from a Lasso regression and a neural network model. The last two models, which can be quickly run using an SQL database, select data from the Federal Reserve Economic Database (FRED) and are fitted (trained) in-sample from 1970 to 2000 to forecast quarterly unemployment rates over 2001 to 2018. The training window is updated in each forecast quarter to include new …