# Unit 3 · Ant colony optimization (ACO)

Subject: Intelligent Systems II

Exam: TEE

Reader: https://deep-learning-study-room.vercel.app/is2/#tee/read/u3-aco

Canonical: https://deep-learning-study-room.vercel.app/read/is2/tee/read-chapter/u3-aco/

Unit 3 · Ant colony optimization for TSP · asked as a 10-mark numerical in both 2025–26 papers

1. [How pheromone feedback guides ant-colony search](https://deep-learning-study-room.vercel.app/read/is2/tee/read/u3-aco--how-ants-work/)
2. [ACO formulas: transition probability, city choice and pheromone update](https://deep-learning-study-room.vercel.app/read/is2/tee/read/u3-aco--formulas/)
3. [Solved PYQ: ACO for a 4-city TSP (Final 2025, 10 marks)](https://deep-learning-study-room.vercel.app/read/is2/tee/read/u3-aco--final-2025/)
4. [Solved PYQ: ACO for a 4-city TSP (Re-exam 2026, 10 marks)](https://deep-learning-study-room.vercel.app/read/is2/tee/read/u3-aco--reexam-2026/)
5. [Practice: the lecture's Ant System example (two different tours)](https://deep-learning-study-room.vercel.app/read/is2/tee/read/u3-aco--lecture-example/)
6. [5/10-mark answer: applications of ACO (explain one)](https://deep-learning-study-room.vercel.app/read/is2/tee/read/u3-aco--applications/)