Skip to Content
Artificial Intelligence with Python Cookbook
book

Artificial Intelligence with Python Cookbook

by Ritesh Kumar, Ben Auffarth
October 2020
Beginner to intermediate
468 pages
9h 39m
English
Packt Publishing
Content preview from Artificial Intelligence with Python Cookbook
Heuristic Search Techniques and Logical Inference

In this chapter, we will introduce a broad range of problem-solving tools. We will start by looking at ontologies and knowledge-based reasoning before moving on to optimization in the context of Boolean satisfiability (SAT) and combinatorial optimization, where we'll simulate the result of individual behavior and coordination in society. Finally, we'll implement Monte Carlo tree search to find the best moves in chess.

We'll be dealing with various techniques in this chapter, including logic solvers, graph embeddings, genetic algorithms (GA), particle swarm optimization (PSO), SAT solvers, simulated annealing (SA), ant colony optimization, multi-agent systems, and Monte Carlo tree search.

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Machine Learning with Python Cookbook

Machine Learning with Python Cookbook

Chris Albon

Publisher Resources

ISBN: 9781789133967Supplemental Content