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AISemester 5AI

Artificial Intelligence Core Concepts

Search algorithms, knowledge representation, expert systems, NLP intro.

15 min read3 sectionsExam-ready notes

Key points

  • Uninformed vs informed search
  • BFS, DFS, UCS, A*
  • Heuristics & admissibility
  • Knowledge representation
  • Agents & PEAS

1. Intelligent Agents

Agent = perceives environment via sensors, acts via actuators.

PEAS: Performance, Environment, Actuators, Sensors

Types: simple reflex, model-based, goal-based, utility-based, learning agents

2. Search Algorithms

Uninformed

  • BFS — optimal if cost=1, O(b^d) space
  • DFS — less memory, not optimal
  • UCS — optimal for positive costs
  • IDS — combines DFS memory + BFS optimality

Informed

  • Greedy best-first — uses h(n) only
  • A* — f(n)=g(n)+h(n); optimal if h admissible & consistent

Admissible heuristic: never overestimates true cost

3. Knowledge & Reasoning

  • Propositional & First-order logic
  • Inference: forward/backward chaining
  • Expert systems: knowledge base + inference engine
  • Uncertainty: Bayesian networks (intro)