Monopoly is a perfect game and a well-created example of pure capitalism in the form of a board, players, and some fake money. The history of Monopoly is intriguing and later in the blog, we will explore artificial intelligence’s inevitable play in the strategy of the best board game ever.
In 1903 a game designer named Elizabeth Magie made a game called “The Landlords Game” which was a precursor to the Monopoly game we all know and love today. Originally the game was meant to be an example of the dangers of giving one person too much power in the American market along with providing hours of long fun with the family. In the 1930s Charles Darrow adapted The Landlords Game and created a version with destinations we know like Park Place and Board Walk while adding a community chest and chance cards for a mix-up of the events of the game. This series of events leads us to Parker Brothers acquiring monopolies rights to create the full board game we have all played.
While the entertainment factor of Monoploy is questionable with ridiculously long play times and the need for multiple friends there, we can all agree that the game comes with some strategy that we could use next family game night to destroy the competition. Players all over the world have come up with the basic strategy of avoiding utilities, buying three houses in a color, shooting for red and orange properties, and ultimately creating a housing shortage to hopefully avoid bankruptcy and your little cousin boasting about his superior real estate knowledge.
Thankfully with the implementation of artificial intelligence in every other aspect of life, we also have been given the implementation into video games and strategy. Man versus machine has been around in strategy gaming for a bit, with the first notable example being in 1996 when IBM’s “deep blue” defeated the world’s best chess player under normal conditions in a game. Since the defeat of Gary Kasparov in chess, machines and artificial intelligence have been able to beat humans in the classic strategy Go, Rubik’s cubes, and many other games. AI and machine learning youtuber, b2studios, made an AI play one million games against other AI bots, to find out the ultimate monopoly strategy!
First, the AI was set to buy everything, trade nothing, and find the winner of the games by buying properties and running the other bots out of competition. With this strategy, the game was up to luck due to no sets being acquired most likely, and all bots owning properties till either stalemate or a slow bankruptcy of other bots. Along with pure luck, this showed what tiles are frequently visited. Due to the number of times the bots ended up in jail, the sets and tiles 12 spots after the jail were most visited during the million games, do with that what you will.
Second bot AI was made to allow for decisions made in the game, and not just random luck on acquiring properties and sets. This was made possible through neural networks, setting the inputs and decisions of monopoly as nodes, and allowing for an evolutionary style of machine learning to happen. The “fitness” of a bot network was rated on a tournament-style bracket, allowing the winners of the tournament to have more offspring in the next cycle of bot networks. When the youtuber allowed the bots to play millions of games, ultimately the best monopoly strategy would be the one on top, through sheer numbers during the evolutionary process.
The total count of games played by the AI was 11.2 million. Throughout the 2-week process of the AI playing, the strategies came together. The AI figured out mortgaging, trading, buildings, and sets to progress to the average monopoly player. A heat map of the AI’s favorite and most winning properties was the railroads at one, oranges at 2, and red and purple at 3 and 4. While there was no perfect way to play Monopoly, using these strategies will give you an edge in the long run over your family at game night. Put it to good use.
While Monopoly is a great game, AI’s use for bettering the world won’t be spent on strategy in games. The incredible speed of pattern recognition has many uses in business and everyday life. Like many examples thought in schools and online, the use of AI is just the tip of the iceberg and hopefully will change the world for the better. I hope you enjoyed the blog and have picked up new tips to win the competition next game night!
Hi Charlie, awesome post. I have definitely taken some tips away for my next monopoly round. When the bot is tasked with decisions in game, it is crazy that it has 11.2 million games of experience and data to pull from. That advantage is insurmountable to a human. Very cool on the cool-creepy scale.
Nice post. Not a huge fan of monopoly for the reasons you mention (and there are so many better games out there), but I do think the ability for AI to train itself by playing games is a huge capability that is only now being tapped – that is, if we think of business as really mostly a slightly more complex game. Oh, and if you haven’t seen the 1982 movie Wargames, it was a game changer for young tech geeks of my generation.
Hey Charlie, great post. I like the design and layout you had for this as well, it was a nice touch. As for Monopoly, I remember vividly looking up how to win in Monopoly. It relied obviously on statistics and it for pretty much similar to what the AI had found. Buying properties like red and orange would more than likely win you the game most of the time because of the frequency you’d land on it.
Hi Charlie! What a great and interesting blog post. Like i’ve been saying on other people’s post, AI continues to surprise me in the fields it’s involving itself in. And this one is definitely one I did not expect.
I personally love Monopoly. I know that it takes HOURS to play, and I’ve never actually “finished” the game properly, but I do get highly competitive when people take a house in my three-color house block. 11.2 million games of Monopoly is insane! I’m glad that the AI was able to figure out the best strategies (and that I decided to read this blog post) because now, I am going to ensure that I aim for the railroads and those specific successful properties. It’ll definitely be cool to see how AI interprets other games and their best strategies on winning.
Hi Charlie! My roommates and I have been playing an unhealthy amount of monopoly recently so this blog post caught my eye. I have been reading about the different strategies for months now and the orange monopoly is always cash. Do you think you could beat AI? After all, the winner typically has the luckiest dice rolls so I think we could give AI a run for its money.
Hey Charlie, great post. I know a lot of the strategy within Monopoly revolves around trading properties, I also know though that when i play on Xbox with my friends it’s almost impossible to trade. Maybe my friends are dumb but it seems like every time I try someone else swoops in and tries to convince them not to. It like i have to take 1 step back to try and move 2 steps forward and even then it ends up being luck. I probably couldn’t beat an AI at the game considering I can barely beat my friends occasionally.
Hey Charlie! It was really cool to learn about the game’s history, from its precursor “The Landlords Game” to Charles Darrow’s version with Park Place and Boardwalk, to Parker Brothers’ acquisition of the rights to make the game we all know and love today. Overall, it was awesome to see how artificial intelligence is changing the game (literally!) when it comes to strategy. I really enjoyed learning about this through your blog post!
I’m on the same boat with Spencer. I can only play the game on xbox with my friends. Board game version almost never finishes. People get distracted, people walk away, people get mad, etc and so the game always ends up abandoned. I’m curious as to what the AI’s trading strategy was to always gather multiple railroads or all the oranges. Was the AI overpaying, scamming the opposing players, or giving fair value trades in order to obtain? (Fair trades almost never happen in real games to be honest)
Hi Charlie! Thanks for sharing your insights on Monopoly and the use of AI in strategy gaming. It’s fascinating to learn about the history of the game and how it has evolved over time. While AI’s use for strategy in games is exciting, I agree that its potential for pattern recognition has far-reaching applications in various fields, including business and everyday life.