As part of my commitment to innovative education at the Faculty of Applied Sciences (FCA-Unicamp), I’ve developed a comprehensive set of materials for our AI Foundations course. These resources aim to bridge the gap between classical artificial intelligence approaches and contemporary developments in the field.
Current Teaching Materials
I’ve recently published a series of Jupyter notebooks designed to provide students with hands-on experience in different AI paradigms:
1. Good Old-Fashioned AI (GOFAI)
This notebook introduces students to the foundational concepts of symbolic AI and logical reasoning systems. It’s crucial for understanding the historical development of AI and the continued relevance of symbolic approaches in modern applications.
2. Reinforcement Learning Implementation
Using the classic Kung Fu game environment, students explore the A3C (Asynchronous Advantage Actor-Critic) algorithm. This practical implementation helps demonstrate how modern AI systems learn through interaction and reward mechanisms.
3. Symbolic Maze Navigation
A hybrid approach combining traditional rule-based systems with modern computational methods, showcasing how different AI paradigms can work together to solve complex problems.
Resources
All teaching materials are freely available on my GitHub repository link. I encourage both students and fellow educators to explore, use, and contribute to these resources.
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