Intelligent Systems II · TEE · about

Portion, source priority and what was checked

Portion, sources and corrections

What this guide covers, where it came from, and every error found in the slides and answer keys

M2

The 8 October class update identifies Fuzzy Logic, GA and PSO, including rules, architecture, advantages/disadvantages, fuzzy operations and numerical work through iteration 2. The confirmed pattern is Q1(a) 2 marks and Q1(b) 2 marks compulsory, plus any two of three 3-mark questions. ACO and GA-for-TSP remain in TEE, not the M2 core.

TEE official syllabus

1. Uncertain knowledge and reasoning: uncertainty, full joint distributions, Bayes, naive Bayes, Bayesian networks, mixture models, GMM, EM and clustering.
2. Fuzzy systems: rules, properties/operations, membership functions, intuition-based fuzzification, mean of maxima, centroid, Mamdani and applications.
3. Evolutionary intelligence: biological basis, GA terms/search space, simple/general GA, encoding/selection/crossover/mutation, stopping, constraints, GA-for-TSP, ACO and swarm optimisation.
4. Reinforcement learning: Markov processes, MRP, MDP, policies, value functions, Bellman equations and applications.

The course policy specifies a 100-mark, three-hour TEE scaled to 50, and 10-mark class tests. The available Final 24 November 2025 and Re-exam 31 January 2026 papers have Q1 compulsory plus any four of Q2–Q7. The next paper’s instructions take precedence.

Source priority

Primary course sources are the AY 2026–27 syllabus and course-policy files, faculty slides and solved-problem material in the 8 October OneDrive archive, the two actual question papers, and the class data supplied in the conversation. The old generated IS2 draft and the separate generated midterm PDF are not authorities for the new teaching sequence.

Handwritten photos can contain inconsistent arithmetic or incomplete conventions. The fan example states its chosen membership functions; the PSO example states minimisation and synchronous updates. Missing selection choices, mutation bits or inconsistent encodings in older papers are labelled explicitly rather than presented as unique answers.

Technical references used for checking conventions

• MathWorks: fuzzy inference process — separation of antecedent operations, implication, aggregation and defuzzification.
• MathWorks: defuzzification definitions — centroid uses the area; MoM uses locations at the maximum.
• MathWorks: particle swarm update — velocity components and best-position memory. Its adaptive neighbourhood implementation is not substituted for the fixed classroom global-best examples.

New worked numerical examples are calculated by reproducible scripts and checked separately. Build checks validate formula rendering and internal routes. This does not justify a promise that no typo can remain, that every future numerical is predictable, or that reading alone guarantees a score.