Presentation Title:
Fundamentals of Artificial Intelligence in Simulation-Based Training
Session Description :
This workshop provides participant experiences to help novices understand and use of various types of AI methods, design training systems with integrated AI capabilities, and evaluate demonstrations of sample AI implementations in training solutions. The authors provide hands-on opportunities for participants to use AI tools (e.g., ChatGPT, TensorFlow, WEKA & MOA) and understand the mechanisms (e.g., transformers) that make AI-based tools and models work. Significant time is also spent discussing data science as an integral practice in developing AI-based models to classify trainee behaviors, predict future simulation states, and recognize/explain the cause of events. Data science in central to human understanding of AI methods, avoiding bias in assessments, and building trust in AI methods. Our workshop agenda follows:
0800-0815 Workshop Introduction (15 minutes) – Bob, Randy & Brice
0815-0845 Workshop Activity: Using Chat GPT (20 minutes) - Brice
0800-0815 Workshop Introduction (15 minutes) – Bob, Brice & Randy
0815-0845 Workshop Activity: Using LLMs (e.g., Chat GPT) to Process Natural Language (20 minutes) - Brice
0845-0900 Understanding the Interplay of Simulation-Based Training and AI (25 minutes) – Bob & Randy
0900-0930 Demonstrations: AI-powered Simulation Systems (30 minutes) - Bob
0930-0945 Understanding the Relationship between Data, Models and Agents (15 minutes) – Brice & Randy
0945-1000 Discussion Activity: Ethical Considerations in AI-powered Simulations (15 minutes) - Bob
1000-1030 Mid-morning Break (30 minutes)
1030-1100 Design Activity: Developing an AI-enhanced Training Simulation (30 minutes) - Brice
1100-1130 Demonstration: Adaptive Instruction (30 mins) - Bob
1130-1145 Discussion Activity: Challenges, Future Directions & Resources (15 minutes) - Randy
1145-1200 Conclusion and Wrap-up (15 minutes) – Bob, Brice & Randy
Intended audience and relevance to I/ITSEC :
This workshop is intended for both managers (non-technical personnel) and aspiring practitioners (engineers and scientists) in the military training systems developer and user communities. Our goal is to identify prevalent intersections of AI and training where simulation-based training benefits from this relationship thourgh more efficient trainee performance (accelerated learning) or effective trainee experiences (higher retention or transfer of skills to operational/work environments).
The content of this workshop provides participants with fundamental knowledge of AI tools and methods, and their applicaton within simulation-baed training systems. AI has a prominent role in simulation-based training as a learner modeling tool (e.g., performance assessments), as an augmentation in the training environment (e.g., intelligent computer-generated forces), as a recommender (e.g., recommended courses of action), and as a tool to optimize adaptive interventions with learners (e.g., modify scenario difficulty or identify teachable moments for delivery post training exercise – After Action Review).
Short statement of benefits participants will gain:
Goal: This workshop provides a fundamental overview of artificial intelligence tools and methods, and their interplay with simulation-based training technology.
Upon completion of this workshop, participants will be able to:
- Comprehend the role and significance of AI in enhancing simulation-based training
- Explore real-world examples of AI applications in simulation-based training across different industries
- Gain knowledge of the underlying AI technologies used in simulation systems
- Recognize the ethical considerations and implications of using AI in training simulations
- Acquire insights into designing AI-enhanced training simulations to address specific training needs
- Discover how AI can provide personalized feedback and assessment in simulation-based training
- Identify the current challenges and limitations of AI in simulation-based training
- Explore potential future directions and advancements in the field of AI in simulation-based training
- Develop a holistic perspective on the role of AI and human trainers in simulation-based training
Keywords: AGENT-BASED SIMULATION;AI;MACHINE LEARNING;SIMULATIONS
Additional Keywords not in the list above: event recognition, trainee models, instructional models, interface models, domain models, large language models
