CSCI-C 463 Artificial Intelligence I
- Prerequisites: None
- Delivery: On-Campus
Goals of artificial intelligence, relations with other fields. Introduction to knowledge representation and inference: predicate calculus, frames, semantic networks, and connectionist representation schemes. Pattern recognition and pattern association. Computer vision. Natural language processing: speech recognition, syntax, and semantics. Heuristic search. Extensive laboratory exercises.
- Explain the history of artificial intelligence (AI) and its cultural and philosophical background.
- Apply AI approaches to achieve AI goals.
- Explain search and representation strategies in AI.
- Evaluate the strengths and weaknesses of algorithms used in AI subfields, such as machine learning, natural language processing, planning, robotics, and autonomous agents.
- Propose AI solutions to real-world problems.
- Write critically about AI research and development topics in the literature.
There is not a syllabus available for this course.