AI and Meta-Heuristics (Combinatorial Optimization) Python

This class is about the basics of artificial intelligence and meta-heuristics with Python, and it talks about how to use them. Learning algorithms can figure out patterns that can help find cancer, for example. We might be able to make algorithms that can figure out how stock prices will move in the market.

There are a lot of algorithms that help you find your way.

This is Section 1: Breadth-First Search (BFS)

• what is breadth-first search?
• In AI, why do graph algorithms need to be used?

Second: Depth-first search (DFS)

• what is a depth-first search algorithm? This is a way to search for things.
• Implementation with iteration and with recursion are two ways.
• the maze-escape app

A* Search Algorithm is in Section 3.

• A* is a search algorithm that helps people find what they want.
• How does Dijkstra’s algorithm work, and how does the A* search work?
• New York distance and Euclidean distance

Meta-heuristics: ###

Simulated Annealing is in Section 4.

• how to find the point where two functions meet
• combinatorial optimization: how to solve them
• the travelling salesman has a problem (TSP)

This is Section 5: Genetic Algorithms.

• It’s important to know what “genetic algorithms” are.
• cross and mutation
• finding a way to solve the knapsack and N queens problems

Section 6 talks about particle swarm optimization (PSO)

• Intelligence that comes from a group of people is called “swarm intelligence.”
• The Particle Swarm Optimization algorithm is a way to find the best way to do something.

Games and game trees: ###

Trees for games are in Section 7.

• In games, what are “trees”?
• how to build game trees

The Minimax Algorithm and Game Engines are in Section 8.

• The minimax algorithm is a way to find the best possible answer.
• What’s wrong with game trees?
• using the alpha-beta pruning method
• chess game

With Minimax, Section 9 is about Tic Tac Toe.

• The Tic Tac Toe game and how it was made
• the minimax algorithm is used
• Pruning with the alpha-beta algorithm

It’s called “reinforcement learning.”

• The basics of reinforcement learning
• value change and policy change
• a problem with exploration and exploitation
• Multi-armed bandits are a problem
• Q is an algorithm that helps people learn.
• with Q, you can learn tic tac toe

People who want to learn how to program in Python quickly should take this crash course.

• The basics of Python programming
• The following is a list of the most important data structures.
• The basics of memory management
• NumPy

Breadth-first search (BFS), depth-first search (DFS), and A* search algorithms are some of the most important graph algorithms. In the first few chapters, we’ll talk about these three types of algorithms.

The next two chapters are about heuristics and meta-heuristics, which are ways to think about them. As well as the theory, we’ll look at how these algorithms work in practice. We’ll look at the N queens problem, the travelling salesman problem (TSP), and a lot of other problems.