Artificial Intelligence #

Artificial Intelligence (AI) is concerned with building systems that can perceive, reason, learn, decide and act in ways that achieve useful goals.

The foundations of AI, its major application areas, four classic ways of thinking about intelligence, important milestones in its development, and some of the risks that accompany increasingly capable AI systems.

Learning Objectives #

explain what intelligence and artificial intelligence mean in practical terms
identify the major disciplines that contributed to AI
distinguish thinking humanly, acting humanly, thinking rationally and acting rationally
explain the idea behind the Turing Test
describe why the rational-agent view is central to modern AI
recognise important application areas and risks of AI

Big Picture #

flowchart TD
    A[Artificial Intelligence] --> B[Human-like]
    A --> C[Rational]
    B --> D[Think like humans]
    B --> E[Act like humans]
    C --> F[Think rationally]
    C --> G[Act rationally]

    style A fill:#C8E6C9
    style B fill:#E1F5FE
    style C fill:#FFF9C4
    style D fill:#EDE7F6
    style E fill:#EDE7F6
    style F fill:#C8E6C9
    style G fill:#C8E6C9

Agent
Explore (all possible solutions)
Environment
Sensor → i/p → Percept
Actuator
Action
Initial State: Source
Transition Model
Random-isation
Learned Info → FACT → Knowledge Base
Backtracking

State Space Transition Diagram / Search Tree
Performance Measure → Numerical Measure (Minimise or Maximise)

M2 → Search M4 → Game M5 → Knowledge → Fact → KB → Inference