High Concept
This project, developed for an assignment, explores the functionality of Action Lists in programming, demonstrating their effectiveness in telemetry gathering and simulation. It highlights how Action Lists can be leveraged to track and simulate events efficiently, offering valuable insights for performance monitoring and system behavior analysis.
Developement Time
2 months
Genre
Card Game
Platform
PC
Team size
1
Engine
Unity
Role
Programmer/Designer
Contributions
Created a basic functional simulation of Texas Hold’em, and different AI types to face off against using action lists.
Used the functional card base to implement a telemetry model to view data from multiple play sessions and balance when needed.
Created a basic animated menu using action lists that are also tracked by the telemetry model. this allows data on how many times a menu item was open and identify the stability of the program
Developing the menu using Action Lists was another enjoyable challenge. Creating block actions and ensuring precise timing to align elements properly provided a valuable learning experience. Utilizing Action Lists to build the menu added an extra layer of polish and refinement to the final product, elevating its overall quality in ways that wouldn’t have been possible otherwise.
This project was primarily focused on exploring the usefulness of Action Lists, but before that, I had to develop the core logic for the game of Texas Hold’em. Implementing the cards and chips using Action Lists was a rewarding exercise that tested my programming skills. The flexibility of Action Lists allowed me to easily tweak object attributes, making the gameplay feel more natural and fluid, enhancing the overall experience.
The telemetry system was designed to simulate real player interactions, allowing us to identify issues such as dominating strategies, unfair advantages, or bugs in both gameplay and the UI. The data on the left displays the number of hands played, the AI types, and their respective outcomes—wins, folds, or losses—along with the remaining chip count in parentheses. This information was crucial for balancing the AI to ensure no type held an unfair advantage over the player. The table on the right shows the frequency of button presses per hand generated by the automated telemetry system, helping us detect potential game crashes or trends in the options menu, and highlighting areas where default settings might need adjustment.