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Intermediate · module I4

Problem Solving and Reasoning: Classical AI

By the end: Model a problem as search, solve it with the right algorithm, and represent and reason with knowledge in logic and probability

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Covers
How AI agents search, play games, satisfy constraints, use logic, plan and reason under uncertainty, before and alongside machine learning
Contents
5 chapters, 16 topics
Time
About 3 hours
Level
Intermediate
Your progress
0 / 16

This module builds on Python Programming for AI. We suggest looking at it first, but the choice is yours.

Chapter 1 Intelligent Agents

  1. 1.1

    Agents and Environments

    Agents, percepts, actions and the PEAS description

    Interactive: describe a self-driving car with PEAS

    10 min Activity
  2. 1.2

    Types of Agents

    Reflex, model-based, goal-based, utility-based and learning agents

    Card sort: which agent type?

    8 minBeing written

Chapter 2 Search

  1. 2.1

    Problem Formulation and State Space

    States, actions, goals and path costs

    Interactive: map a puzzle as states

    10 minBeing written
  2. 2.2

    Uninformed Search

    Breadth-first, depth-first and uniform-cost search

    Interactive: race BFS and DFS through a maze

    15 min Activity
  3. 2.3

    Informed Search and A*

    Heuristics, greedy best-first search and A*

    Interactive: A* on a city map

    f(n) = g(n) + h(n)

    15 min Activity
  4. 2.4

    Local Search and Optimisation

    Hill climbing, simulated annealing and genetic algorithms

    Interactive: climb to the highest peak

    12 min Activity

Chapter 3 Games and Constraints

  1. 3.1

    Adversarial Search: Minimax

    How a program plays a two-player game

    Interactive: play tic-tac-toe against minimax

    15 min Activity
  2. 3.2

    Alpha-Beta Pruning

    Skipping moves that cannot matter

    Interactive: watch branches being pruned

    10 minBeing written
  3. 3.3

    Constraint Satisfaction Problems

    Variables, domains, constraints and backtracking

    Interactive: solve a sudoku and a map colouring

    12 min Activity

Chapter 4 Knowledge and Logic

  1. 4.1

    Propositional Logic

    Statements, connectives, truth tables and inference

    Code: a truth-table checker

    P ⇒ Q ≡ ¬P ∨ Q

    12 min Activity
  2. 4.2

    First-Order Logic

    Objects, relations and quantifiers

    Exercise: translate English into logic

    ∀x Human(x) ⇒ Mortal(x)

    12 minBeing written
  3. 4.3

    Knowledge Representation and Expert Systems

    Rules, frames, semantic networks, ontologies and inference engines

    Code: a small expert system

    12 min Activity
  4. 4.4

    Automated Planning

    Actions, preconditions and effects, and finding a plan

    Interactive: plan a robot's tasks

    10 min Activity

Chapter 5 Reasoning Under Uncertainty

  1. 5.1

    Probabilistic Reasoning

    Using probability and Bayes' rule to make decisions

    Code: a diagnosis helper

    P(cause|effect) ∝ P(effect|cause)P(cause)

    12 min Activity
  2. 5.2

    Fuzzy Logic

    Degrees of truth and fuzzy rules

    Interactive: a fuzzy fan controller

    μ(x) ∈ [0, 1]

    8 min Activity
  3. 5.3

    Module Review and Assessment

    Exercises and a scored quiz

    Graded quiz

    15 minBeing written