Introduction to Artificial Intelligence: Course Content

White Board
What is AI? Moving Answer; Traditional Answer; Agentic Answer; Philosophical Answer; Historical Answer; Structural Answer
Sensors
- Knowledge sources: Human (we think we know it all); Environment (temperature, sights, sounds, animals, ocean, etc.); Machine (data loggers, IoT, machine learning, etc.)
- Source structures: Raw data (sampling, data logs, etc.); Formal representations (math, engineering, science, etc.); Informal representations (natural language, images, sounds, etc.)
- Data Collecting (Data Science)
- Natural Language Processing
  - Views from IBM; Diyi Yang; Behrooz Mansouri; Vinay Chaudhri
  - Creating a KG using NLP.
  - Language to Logic
Knowledge Representation
- The Status of Knowledge
- Vector Data
- Logic (R&N Ch.8-9)
  - The TPTP World
  - Logic: Propositional; First-order; Typed First-order
- Knowledge Graphs (R&N Ch.10)
  - Views from IBM; neo4j; Wikipedia
  - Creating a KG using NLP.
- Taxonomies and Ontologies
  - Taxonomy views from Wikipedia; YAGO
  - Taxonomies in LLMs
  - Ontology views from Adam Pease; SUMO
Learning
Reasoning
Actuators
Ethics
Conclusion