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Overview
Want to build a strong theoretical foundation but sick of long readings?
Gone are the days where you have to spend hours reading thick textbooks and readings. With zyBooks, you can learn more about your selected topic with minimal reading, maximum interactivity.
Preferred Choice
80% of surveyed students preferred zyBooks over regular textbooks.
Better Learning
Studies show that students learn 118% more with the minimal text model in only one lesson.
Proven Results
On average, zyBook users improved grades up to ⅔ and read 74% more than users of regular textbooks.
Topics
Data Analytics
Computer Science
What Our Students Say
Testimonials
FAQ

INTRODUCTIONIntroduction What is AI good for?

GRAPHSEARCH ALGORITHMSBreadthfirst search introduction Breadtfirst search implementation Depthfirst search introduction Depthfirst search implementation I  with stack Depthfirst search implementation II  with recursion Enhanced search algorithms introduction Iterative deepening depthfirst search (IDDFS) A* search introduction

BASIC SEARCH & OPTIMIZATION ALGORITHMSBruteforce search introduction Bruteforce search example Stochastic search introduction Stochastic search example Hill climbing introduction Hill climbing example

METAHEURISTIC OPTIMIZATION METHODSHeuristics VS metaheuristics Tabu search introduction Simulated annealing introduction Simulated annealing  function extremum I Simulated annealing  function extremum II Simulated annealing  function extremum III Travelling salesman problem I  city Travelling salesman problem II  tour Travelling salesman problem III  annealing algorithm Travelling salesman problem IV  testing Genetic algorithms introduction  basics Genetic algorithms introduction  chromosomes Genetic algorithms introduction  crossover Genetic algorithms introduction  mutation Genetic algorithms introduction  the algorithm Genetic algorithm implementation I  individual Genetic algorithm implementation II  population Genetic algorithm implementation III  the algorithm Genetic algorithm implementation IV  testing Genetic algorithm implementation V  function optimum Swarm intelligence intoduction Partical swarm optimization introduction I  basics Partical swarm optimization introduction II  the algorithm Particle swarm optimization implementation I  particle Particle swarm optimization implementation II  initialize Particle swarm optimization implementation III  the algorithm Particle swarm optimization implementation IV  testing

MINIMAX ALGORITHM  GAME ENGINESGame trees introduction Minimax algorithm introduction  basics Minimax algorithm introduction  the algorithm Minimax algorithm introduction  relation with tictactoe Alphabeta pruning introduction Alphabeta pruning example Chess problem

BUILDING TICTACTOEAbout the game Cell Constants and Player Game implementation I Game implementation II Board implementation I Board implementationj II  isWinning() Board implementation III Minimax algorithm Running tictactoe

INTERVIEW: SINGAPOREAN EXPERTBackground of Expert Information and Communication Technology in Singapore
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