Brandon Druschel's Work Site for CSC 466 - Topics in Symbolic AI

Welcome to my AI2 web site! Here you can find various content relating to Topics in Symbolic AI, which is currently being taught by Craig Graci. This includes documents and programs by myself, as well as some external resources, pertaining to AI and Lisp programming, that you may find helpful.

The External Resources section of this page is divided into two sections; Elaboration and Enrichment. The former will reference items that pertain to the technical content of the course, and the latter will point to interesting items that are less technical in nature, like TED talks or YouTube videos or magazine articles.

About Me:

I am a senior Computer Science student that is enrolled in SUNY Oswego. I'm currently working on a Bachelor of Science degree, hoping to graduate by May 2019!

I figured CSC 466 would be a natural step up from CSC 416, hence me registering for it. Besides that, I found AI and its surrounding topics to be very interesting. Expanding my knowledge to symbolic AI and further developing my Lisp skills would also be a valuable learning experience.

Course Assignments:

• Learning, Machine Learning, Symbolic Machine Learning [PDF]
• Tic-Tac-Toe
  1. Task 1 - Play [Source] [Demo] [Analysis]
  2. Task 2 - Visualization, Analysis & Statistics [Source] [Demo]
• Research/Programming Project Planning
  1. Proposal One: Self-Navigating AI
  2. Proposal Two: Peg Solitaire LM
  3. Project Specifications
• Peg Board Learning Machine
  Source: [pegs.l]
  1. Task 1 — Global List [Code] [Demo]
  2. Task 2 — Random Move Generator [Code] [Demo]
  3. Task 3 — Draw a Peg Board [Code] [Demo]
  4. Task 4 — Labels & Constraints [Code] [Demo]
  5. Task 5 — Determining a Valid Move [Code] [Demo]
  6. Task 6 — Make Your Move [Code] [Demo]
  7. Task 7 — State of the Game [Code] [Demo]
  8. Task 8 — Mutation [Code] [Demo] [Labelled Demo]
  9. Task 9 — Crossover [Code] [Demo] [Labelled Demo]
  10. Task 10 — Fitness Metric [Code] [Demo 1] [Demo 2]
      Demos 1 and 2 use the first and second fitness metric, respectively.
  11. Task 11 — Individual Class [Code] [Interactive Demo] [Encapsulated Demo]
  12. Task 12 — Population Class [Code] [Interactive Demo] [Encapsulated Demo]
  13. Task 13 — Incorporate Mutation [Code] [Interactive Demo] [Encapsulated Demo]
  14. Task 14 — Copy [Code] [Demo]
  15. Task 15 — Crossover (2) [Code] [Demo]
  16. Task 16 — The Genetic Algorithm [Code] [Demo 1] [Demo 2] [Demo 3]
      Demo 1 uses remaining pegs as fitness, while the latter two uses separation of pegs as a fitness metric.
• Symbolic Machine Learning Enrichment Assignment
  [PDF] [PowerPoint]
• Peg Board LM Presentation
  [PDF] [Google Slides]
• Peg Board LM Paper
  [PDF]

External Resources:

• Elaboration
• AI - Wikipedia
• Lisp - Wikipedia
• Common Lisp the Language, 2nd Edition (Guy Steele)
• Practical Common Lisp (Peter Seibel)

• Enrichment
• ComputeMusic(now): Andrew Sorensen at TEDxQUT - YouTube
• Can we build AI without losing control over it? - TED
• Machine Learning & Artificial Intelligence: Crash Course Computer Science