AI-generated Hangman: A fun guessing game

The AI-generated code for the Hangman game is a simple implementation using HTML, CSS, and JavaScript. The game then allows the player to guess letters, and the code checks if the letter is valid and if it has not been guessed before.

Introduction:

Hangman is a classic word guessing game that has been enjoyed by generations. With the advancements in artificial intelligence (AI), it is now possible to generate a version of the game with just a few lines of code. In this article, we will discuss an experiment where an AI was guided to create a basic web game of Hangman, the project summary generated by the AI, the command given to the AI, and the limitations of the AI-generated code.

A developer interacts with AI-generated code prompts in a neon holodeck games room

Hangman Game

Word:

Guesses:



Traditional Hangman Rules:

Traditional Hangman is a simple game that can be played by people of all ages. The player tries to guess a word by suggesting letters, one at a time. Each incorrect guess results in a part of a “hangman” figure being drawn. If the player guesses the word before the figure is completed, they win. Otherwise, they lose.

AI Code Experiment:

The AI-generated code for the Hangman game is a simple implementation using HTML, CSS, and JavaScript. The code starts by generating a random word from a pre-defined list of words.

The game then allows the player to guess letters, and the code checks if the letter is valid and if it has not been guessed before. If the letter is valid and new, it is added to the list of guesses, and the code checks if it is part of the random word. If the letter is part of the word, it replaces the corresponding underscores in the word display with the letter. If the letter is not part of the word, it decreases the remaining guesses counter and shows a message informing the player of how many guesses they have left.

The game continues until the player wins by correctly guessing the word or loses by running out of guesses. The player can play again by clicking the “Play Again” button, which generates a new random word and resets the game variables.

Command given to AI:

The initial command prompt given to ChatGPT-3 was simple yet specific: “generate the code for a Hangman game with play again button and random word list.” Despite the simplicity of the command, the AI was able to generate a functional version of the game that met all of the specified requirements.

While some guidance was provided to the AI in terms of style, improvements, and fixes, the majority of the code was indeed generated in response to the initial command.

It is worth noting that while AI-generated code can provide a quick and easy starting point for development projects, it is still important for developers to thoroughly review and test the code to ensure that it meets the necessary requirements and functions properly. In this case, some modifications and improvements were necessary to address limitations and enhance the functionality of the game.

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Limitations of the AI-generated code:

While the AI-generated code is able to provide a basic version of the Hangman game, there are limitations to its functionality.

  • Currently, the code does not account for capital letters, which can limit the range of words that can be used in the game. Although we could modify the code to include them, we decided to stick with the AI-generated code.
  • There is no hangman image included in the game as ChatGPT is not able to create images. To work around this, we asked ChatGPT to use characters to represent the hangman figure, but it was unable to complete the script due to the maximum coding line limit of ChatGPT.

Possible Improvements

Improvements to the AI-generated Hangman game could include adding a feature that allows the user to choose the difficulty level or category of words. For example, the user could choose between easy, medium, or hard difficulty levels or choose a specific category such as animals, countries, or movies.

Another improvement could be to add a feature that allows the user to input their own list of words to be used in the game. This would allow users to customize the game to their liking and add an extra element of personalization.

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Conclusion

Overall, we consider this experiment to be a success, as ChatGPT was able to generate a fully functional Hangman game, despite not fulfilling all of the initial requirements. It is a great starting point for beginners who are learning to code and want to create a simple web game. While there were some limitations to the AI-generated code, with some improvements and modifications, it could become an even more engaging and customizable game.

It is worth noting that the success of this experiment highlights the potential of AI in the field of web development. As AI continues to advance and improve, it is likely that we will see more AI-generated code in web development projects. While there are limitations to what AI-generated code can currently do, it can serve as a valuable starting point and foundation for beginner developers, allowing them to quickly and easily create functional web applications.

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