Adaptive parameter system for Emerging Serious Games using Cultural Algorithms, developed with Qt API as part of a Doctoral Thesis.
This system dynamically adapts serious game parameters in real-time based on player behavior and learning performance in smart classroom environments.
Project: SAP-AC Type: Doctoral Research Approach: Cultural Algorithm Domain: Emerging Serious Games Framework: Qt API Language: C++ Context: Smart Classroom Adaptive Systems
C++ Qt API Artificial Intelligence Cultural Algorithms Evolutionary Computation Serious Games Adaptive Systems Smart Classroom
One of the main limitations of serious games is their reduced ability to adapt to players during gameplay. Emerging Serious Games address this limitation by enabling real-time adjustment of game parameters.
This project proposes an adaptive parameter system based on Cultural Algorithms. The system dynamically modifies serious game parameters using information obtained from the learning process.
The architecture allows serious games to adapt to:
Player behavior Learning performance Educational objectives Gameplay time Scoring targets
Cultural Algorithms extend evolutionary computation by introducing a belief space that stores knowledge acquired during evolution.
The system includes:
Population Space Belief Space Communication Protocol Knowledge Sources Evolutionary Adaptation
Cultural Algorithm implementation Real-time parameter adaptation Smart classroom integration Player behavior analysis Learning process monitoring Dynamic difficulty adjustment Optimal gameplay time estimation Educational objective optimization
Computes optimal parameter values
Adjusts serious game parameters in real-time
Collects player performance data
Stores learned parameter configurations
Connects algorithm with serious games
This repository is part of the research presented in the following publications:
IEEE Publication
Adaptive parameter system for emerging serious games using cultural algorithms
https://ieeexplore.ieee.org/abstract/document/9566787
SAGE Journal Publication
Cultural algorithm-based adaptive system for emerging serious games in smart classroom environments
https://journals.sagepub.com/doi/abs/10.1177/13272314241295946
The system was evaluated in a smart classroom environment where multiple serious games were dynamically adapted.
The algorithm successfully:
Adjusted game parameters Adapted to student behavior Optimized playing time Improved learning performance Achieved educational objectives
Development of an architecture based on Cultural Algorithms that adapts serious game parameters to the characteristics of players in a smart classroom.
The results show that serious games dynamically adapt to student behavior and learning progress.
Clone repository
git clone https://github.com/Fridnansen/SAP-AC.git
Open project in:
Qt Creator Qt + CMake Qt + qmake
Build project and run main file.
Artificial Intelligence Cultural Algorithms Adaptive Systems Serious Games Evolutionary Computation Real-time Parameter Optimization Smart Classroom Systems Qt Development
Doctoral Research Artificial Intelligence Adaptive Serious Games Cultural Algorithms Educational Technology
Francisco José Díaz Villarreal
PhD Applied Sciences
Software Engineer | AI Researcher | Serious Games Developer