Designing a Quantum Computing Board Game

Maryam Ashoori
Jul 10, 2018 · 6 min read
Eager to Play? Make your own copy of Entanglion!

Quantum computing is a rapidly-maturing field that uses quantum-mechanical phenomena such as superposition and entanglement to perform computations considered intractable for classical computers.

If you didn’t understand a word of the previous sentence, you’re not alone! My first introduction to quantum computing was when I was a university student and a friend of mine told me he was studying quantum computing. I asked him what this was, and after five minutes, I still had no idea.

Fast forward to mid-2016, I joined the team in IBM Research that developed the IBM Q Experience and QISKit, and needed to get up to speed on exactly what quantum computing was about. I read all the online guides and tutorials I could find and watched countless videos, but every time I thought I understood something, I found myself back at the beginning, not having a strong grasp of the material. Plus, to be honest, the material was difficult to understand and veiled behind a wall of mathematical expressions. I longed for a better way to educate someone on the fundamental principles of quantum computing.

Quantum + Board Game = Awesome!

One weekend, my husband (also a researcher with IBM) and I purchased a new board game to play together. The box claimed the game took two hours to play, but we spent much more time than that learning the rules, trying to play through a turn, making mistakes, and correcting them by constantly referring back to the rulebook. By the end, we were able to play through a full game (and as is customary, I won!), but upon reflecting on this process, we were both amazed by how much time and energy we put into learning a game with arbitrary rules. What if we could do the same thing, but learn something along the way?

This is how the idea for a quantum computing board game was born.

Designing a game is hard. Designing a quantum game? Much harder.

My husband and I worked together to design a board game with two goals: it had to be fun, and it had to teach the players about fundamental principles of quantum computing. Both of us have a research background in human-computer interaction (HCI), which aims to understand and improve how people interact with and through technology. We relied on two main research methods from HCI in developing our game: paper prototyping and iterative design.

Designing on paper enabled us to make rapid changes to the game as we tested new mechanics and rules. Our early versions of the game borrowed many components from other board games we enjoy, plus a lot of sticky notes and paper cutouts. After we settled on game mechanics that felt fun, we showed our prototype to a group of quantum scientists in our lab at IBM Research to get feedback on the science aspects. Their favorite comment to us was, “this is not quantum,” sending us back to the drawing board to think of new ways to represent a quantum system in cardboard. We ended up creating five major iterations of our board game before our quantum scientists gave us their seal of approval.

The first version of our board game borrowed components from Carcassone, another game we enjoy.
The third iteration of our board game is very colorful and was fun to play, but our quantum scientists felt it was “not quantum enough.”
Dr. Charles Bennett, an IBM Fellow and pioneer in the field of quantum information science, gives us feedback on the second iteration of our game.
In iteration four, we settled on a sci-fi theme in which players move their spaceships from planet to planet to retrieve components of a quantum computer.

Learning objectives

When designing a game to teach a highly technical subject, we thought hard about whether the objective was to simply introduce players to high-level conceptsin quantum computing, or to go deep into the intricate details of quantum computing algorithms. In order to make our game enjoyable to a broad range of players, we opted to place our emphasis on familiarity with high-level concepts (called conceptual mastery) rather than focusing deeply on the particulars of quantum algorithms (called technical mastery). We decided our game should expose players to these fundamental concepts in quantum computing: qubits and quantum states, superposition, entanglement, measurement, error, and the different kinds of hardware and software components involved in building a real quantum computer. Early in our design process, we made the goal of our game to be to construct a quantum computer from it’s constituent components!

Cooperative or Competitive?

Many board games are competitive, pitting player against player in a battle of wits and strategy. Since our objective was to make an educationalgame, we felt that the best learning outcomes would happen when players worked together in order to accomplish the game’s objective. We made this decision from observations we made during our playtesting sessions — players often asked each other questions like,“what happens if I play this?” and “how does this thing work?” The discussions that followed often led to a stronger understanding of the game’s underlying mechanics, leading to a strong understanding of the mechanics of quantum computing. These are exactly the kinds of discussions we wanted players to have while playing our game, and thus we made our game cooperative.

Calibration of Game Difficulty

The quality that makes a game great lies in its ability to challenge the player just the right amount at just the right times. Games that are too easy are trivial and unsatisfying; games that are too difficult can be frustrating, leading to abandonment. Thus, we had a strong desire to ensure the game was just challenging enough to be fun, but not too difficult as to cause players to give up from frustration or dissatisfaction.

One challenge we faced in calibrating the difficulty was having enough people playtest it in order to be confident that the game wasn’t too easy or too difficult. To overcome this challenge, we actually implemented a simulator for the game and AI players who could play it together. We ran thousands of game simulations to help us calibrate the difficulty of the game, making tweaks and running more simulations to understand their effect. Although AI players don’t truly capture how people would play our game, we empirically decided that win rates of 50–60% for an AI team corresponded to an adequate level of challenge for human players.

Enter Entanglion

After you played the game, go to QISkit and make your own game, and learn more about quantum computing by programing a real one.

Design at IBM

Stories from the practice of design at IBM

Maryam Ashoori

Written by

Excited new mom. Research scientist at IBM Research AI, known as IBM's "cool things" czar!

Design at IBM

Stories from the practice of design at IBM

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