by Daniel Jallov | Released December 2017 | ISBN: 9781788472180

Understand Graph Algorithms to create your own game in AIAbout This VideoSolve the most common graphs problems with increasing complexity of the algorithms.Implement learning algorithms that work on graphs and concepts to build your own games in AIA comprehensive course to gain better understanding of the fundamental concepts and graph algorithms used in gamesIn DetailGraphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect a set of computers into a network you will need algorithms on graphs.For using the efficient algorithm to automatically find communities and opinion leaders on Facebook, you're going to work with graphs and algorithms on graphs. This course will serve as an introduction to graphs and present their increasingly complex algorithms that work on graphs. In the course, you will start by understanding how graphs can be used in games to represent various states and how searching graphs can help us. The course will introduce you to pathfinding, which is one of the most commonly solved problems in game AI. The course will then show you how to Optimize the pathfinding.Finally, at the end of the course, you will learn the concept of meta-heuristics which can be used to find general solutions in complex domains. Show and hide more

1. Chapter 1 : Understanding Graphs
   • The Course Overview 00:03:25
   • What Are Graphs? 00:06:35
   • Implementing Graphs 00:09:15
   • Implementing Trees 00:05:46
   • How Can We Use Graphs in Games? 00:04:22
2. Chapter 2 : Searching in Graphs
   • What Are We Searching for? 00:03:21
   • Using Breadth-First Search (BFS) 00:03:38
   • Implementing BFS on Regular Graphs 00:07:50
   • Using Depth-First Search (DFS) 00:04:36
   • Implementing DFS 00:07:06
   • Example - A Simple Puzzle Game 00:12:16
3. Chapter 3 : Working with Pathfinding
   • What Is a Shortest Path? 00:03:58
   • Dijkstra's Algorithm 00:05:39
   • Implementing Pathfinding in General Graphs 00:04:36
   • Representing Grids and Mazes as Graphs 00:04:46
   • Implementing Pathfinding in Grids 00:11:19
4. Chapter 4 : Optimization Heuristics
   • What Is a Heuristic? 00:04:10
   • Greedy Heuristic - Best First Search 00:07:58
   • Finding a More Balanced Heuristic - A* Search 00:06:02
   • Implementing A* Search 00:05:35
   • Search-Space Optimization - Bi-directional Search 00:09:05
5. Chapter 5 : Creating a Pacman-Like Game
   • Defining the Game Logic and AI 00:04:02
   • Implementing "random" Movement for Ghosts 00:09:23
   • Implementing Pathfinding with a Lag 00:03:43
   • Using Dijkstra's Algorithm for Fleeing Ghosts 00:08:55
   • The Final Game 00:04:35
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