Different portion: This page is a light midterm brush-up only. Your main preparation for FINAL TERM is under Final Topics and Sample Papers.

Before-mid syllabus · quick recall

Midterm ideas (short)

What is AI? (60-second version)

Simple English

AI systems perceive, reason, and act to achieve goals. An agent gets percepts from the environment and chooses actions. PEAS = Performance measure, Environment, Actuators, Sensors.

Environments can be fully/partially observable, deterministic/stochastic, episodic/sequential, static/dynamic, discrete/continuous, single/multi-agent.

Roman English

AI agent environment se percepts leta hai aur actions choose karta hai. PEAS yaad rakho. Environment types (observable, deterministic, etc.) MCQs mein aate hain.

Search (brush-up)

Simple English

Uninformed: BFS, DFS, UCS — no goal heuristic.

Informed: Greedy Best-First, A* — use heuristic h(n). A* with consistent heuristic is optimally efficient among optimal algorithms in standard settings.

Connect to finals: Genetic Algorithms are another way to search huge spaces when classical search struggles.

Roman English

BFS/DFS/UCS = uninformed. A*/Greedy = informed (heuristic). Final mein GA bhi search/optimization ka tool hai — alag style.

How this links to finals

Midterm built the “agent + search” mindset. Finals push into evolution (GA), knowledge & logic, and learning (NN, Bayes, K-NN, K-means). Don’t spend finals week re-reading midterm chapters in depth — skim this page, then return to final packs.

Go to final topics