Graph Algorithms for AI in Games

Graphs 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.

The video is packed with step-by-step instructions, working examples, and helpful advice. You will learn about Graph Algorithms for AI in Games. This practical course is divided into clear byte size chunks so you can learn at your own pace and focus on the areas of most interest to you.

What You Will Learn

Make graphs to represent your game state
Use the breadth first search on your regular graphs
Implement the depth first search with your usual graphs
Use pathfinding in your grid and mazes
Work with optimizing the Heuristics in your game
Implement A* Search for a more balanced Heuristics
Create your very own Pac Mac like Game

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