1. Monopoly Agent Strategy Simulation Nicholas Loffredo

2. Overview My project is to make a simulation of Monopoly with agents that can negotiate with each other, buy titles and houses/hotels, mortgage properties, etc. and find the optimal strategy for Monopoly.

3. Current State Computer buys/mortgages/unmortgages properties and buys/sells houses based on aggressiveness levels Monopoly, Matrix, Wins Display Mostly finished Monopoly rules/game Computer changes aggressiveness levels Multiple games in one run Read in aggressiveness values and wins from text file Agents trades properties for cash Agents auction properties

6. Results Player 0 (learning agent) is learning significantly Limited due to a number of factors, most likely  Structure of aggressiveness chart  Inflexible  Does not allow for factoring in state of game, number of monopolies, etc.

7. Further Research Allow trading properties for other properties Fix a bug with trading/auctioning Test different structures of reinforcement learning Test an expert systems based AI vs. my reinforcement learning AI Attempt to implement aggressiveness chart idea for other games