Module 04
Classical AI — Agents, Search & Knowledge Representation
The pre-neural artificial intelligence that still runs in production: what the field decided intelligence means, rational agents and their environments, systematic, heuristic and local search, and the symbolic and probabilistic ways of representing what a system knows.
14 topics ~63 h estimated learning time
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- 4.1 What artificial intelligence is, and the four ways to define it
Foundation · 3 h
- 4.2 How AI got here — and the two winters
Foundation · 3 h
- 4.3 Agents, rationality and PEAS
Foundation · 4 h
- 4.4 Task environments and the four agent types
Core · 4 h
- 4.5 Problem-solving agents and problem formulation
Core · 4 h
- 4.6 Judging a search strategy
Core · 3 h
- 4.7 Uninformed search
Core · 6 h
- 4.8 Informed search: greedy best-first and A*
Core · 6 h
- 4.9 Admissible and consistent heuristics
Core · 5 h
- 4.10 Local search and optimisation
Core · 6 h
- 4.11 Approaches to knowledge representation
Core · 4 h
- 4.12 Semantic networks, extended semantic networks and frames
Core · 5 h
- 4.13 Bayesian networks: representation and inference
Core · 5 h
- 4.14 Hidden Markov models
Core · 5 h