AI Learns To Play Monopoly

The Science of Winning at Monopoly: What AI Taught Us About the World's Most Famous Board Game

Monopoly – a game that has sparked countless family arguments and created lifelong memories for generations. Whether you look back on it fondly or with trauma-induced flashbacks, one question has probably crossed your mind: what's the best way to actually win at this iconic board game?

After running millions of AI simulations and crunching the numbers, we finally have some fascinating answers that might surprise you.

 The Fundamental Reality: You're Not Really in Control

The first harsh truth about Monopoly is that it's not chess. You simply aren't in control of everything your player does. When it comes to movement, you have virtually no influence over where you'll land – it's determined entirely by dice rolls.

There's only one tiny way to influence your positioning: the probability of rolling doubles increases the longer you stay in jail, making you more likely to land on even-numbered squares. It's not much, but it's literally all you've got.

The Million-Game Experiment

To understand Monopoly's deeper mechanics, we created AI bots and had them play one million games. These bots followed a simple strategy: buy everything, trade nothing, build houses when possible, and only mortgage when desperate.

The results revealed some shocking truths about the game's fairness.

The Going-First Advantage Is Massive

While everyone knows going first provides an advantage, the scale is staggering:

- With 4 players: 5% difference between first and last

- With 3 players: 18% difference  

- With 2 players: 57% difference

That's right – in a two-player game, going first gives you a massive advantage that makes the game fundamentally unfair.

 Most Games Never End

Perhaps most surprising was how often games ended in stalemates:

- 4 players: 70% stalemate rate

- 3 players: 42% stalemate rate  

- 2 players: 4% stalemate rate

Without trading, most games become endless slogs where nobody can acquire complete property sets to inflict meaningful damage.

The Surprising Truth About Property Values

The heat map of where players land most frequently tells an interesting story. Jail is by far the most visited location – not because it's punishment, but because there are so many ways to get there (cards, rolling three doubles, the "Go to Jail" space, or choosing to stay).

This positioning data revealed something unexpected about property values. When we measured which properties belonged to winners most often, the results were shocking:

**1st Place: Dark Blues (Boardwalk/Park Place)**

No surprise here – these expensive properties with high rents are always powerful.

**2nd Place: Browns (Mediterranean/Baltic)**

Wait... what? The worst properties on the board somehow became the second-most valuable for winning games.

The explanation is brilliant in its simplicity: in games without trading, acquiring a complete set is extremely difficult with three-property groups, since you need to land on all three before opponents do. Two-property sets like the browns are simply easier to complete by chance alone.

 Teaching AI to Trade: The Neural Network Approach

Since our no-trading bots weren't playing real Monopoly, we created a sophisticated AI using NEAT (NeuroEvolution of Augmenting Topologies) – essentially teaching neural networks to play Monopoly through evolution.

After 11.2 million games (equivalent to 1,600 years of human play), the AI went through fascinating learning phases:

 Phase 1: Chaos

The AI discovered that staying in jail was good, then overcorrected by bidding $3,000 on every property and losing spectacularly.

Phase 2: Learning the Basics  

It figured out building houses and unmortgaging, becoming more aggressive when winning and passive when losing.

Phase 3: The Mortgage Everything Strategy

In a bizarre twist, the AI tried mortgaging every single property it owned, guaranteeing draws in every game. This didn't last long.

Phase 4: Sophisticated Play

The AI developed human-level strategies, making even trades and playing intelligently.

Phase 5: The Auction Trick

In its final evolution, the AI discovered an advanced strategy of auctioning everything and bidding almost nothing – a move that showcased its deep understanding of the game's mechanics.

The Final Verdict: What Properties Should You Target?

After two weeks of intensive AI training, here are the properties that emerged as favorites:

**Top Tier:**

- **Orange properties** (St. James Place, Tennessee, New York) – The AI's absolute favorite set

- **Railroads** – Especially the first railroad, which became the AI's favorite single property

- **Red and Purple sets** – Consistently strong performers

- **Boardwalk/Park Place** – Still valuable despite their high cost

The AI's analysis confirmed much of what experienced human players have long suspected, validating that our intuitions about the game aren't entirely wrong.

 Key Takeaways for Better Monopoly Play

1. **Trading is essential** – Without it, you're just playing an expensive lottery

2. **Orange properties are gold** – They hit the sweet spot of rent-to-cost ratio and landing probability  

3. **Railroads are underrated** – Consistent income throughout the game

4. **Going first matters more than you think** – Especially in smaller games

5. **The brown properties aren't as terrible as they seem** – In the right circumstances

 The Bottom Line

Monopoly is fundamentally a game of probability and negotiation. While luck plays a huge role, understanding the underlying mathematics can give you a significant edge. The AI's journey from chaotic beginner to sophisticated player mirrors how humans learn the game – through experience, pattern recognition, and gradual understanding of complex interactions.

Next time you sit down for a game of Monopoly, remember: it's not just about the dice rolls. It's about understanding probability, making smart trades, and knowing which properties will actually help you win. The orange properties are waiting for you – and now you know why they're special.

*Who knew that teaching a computer to play Monopoly would validate what the best human players figured out decades ago? Sometimes the old wisdom really is the best wisdom.*

-  **#TradeToWin #AggressiveTrading #StalemateRate**  

-  **#OrangeSetOP #HouseHustle #TrainStationsRule**  

- **#AITestedStrategies #JailExitStrategy #11MillionGames**