1 – Dynamic scenarios:
Artificial intelligence can adapt the scenario based on players’ choices and performance. Hence, the players’ decisions influence the scenario. The learner lives a more personalized adventure, making the experience more immersive.
AI can simulate environments where players have to make decisions based on varied and unpredictable data, enhancing decision-making skills in realistic situations.
2 – Dialogue simulation:
Using language processing technologies, AI:
- enables interactions and dialogues with non-player characters (NPC)
For example: a customer who interacts with the player (for sales training or “product” training)
- helps and accompanies the player through an avatar during the course, offering more realistic and engaging dialogues.
For example: a colleague or manager who can give you advice when you’re stuck and whom you can talk to.
3 – Adapting difficulty levels:
By analyzing players’ responses, Artificial Intelligence adapts the level of challenges to their level of knowledge. This creates a personalized learning experience that can maintain engagement and create effective pedagogy for different types of learners.
4 – Real-time feedback:
AI coupled with Serious Games can provide users with immediate feedback on their actions. This can help reinforce positive behaviors, correct mistakes and encourage self-assessment.
5 – Response analysis:
The AI can synthetize the data retrieved (time spent, answers given at each stage) to provide the learners with a performance summary.
These summaries include scores, identified strengths and weaknesses, as well as specific advice for progress.
How do you create an AI for Serious Games?
Our creative team will collaborate with your teams to co-create the AI model to ensure that the AI meets your expectations and your training challenges for your Serious Game.
Together, we will define the objectives, build the AI model, train it and adjust the parameters to optimize the performance and the costs.
It’s an iterative process that requires close collaboration between the two parties, particularly to improve the quality of the data given to the AI, and working to refine the model until we achieve the most reliable AI possible.