Foundations of AI Algorithms in Java: Search, Optimization, and Games

Understanding how computers solve complex pathfinding, optimization, and strategic decision-making problems is the cornerstone of artificial intelligence. This text-based course guides you through the core concepts of AI algorithms, demonstrating how to implement them step-by-step using Java. You will transition from writing basic programs to crafting intelligent algorithms that can navigate mazes, optimize complex functions, and play classic games. By studying clear written explanations and examining structured code snippets, you will gain a deep, intuitive understanding of how classic AI works under the hood. What you'll learn: - Understand foundational graph theory and implement classic search algorithms like Breadth-First Search (BFS) and Depth-First Search (DFS). - Apply heuristic search techniques using the A* algorithm to solve pathfinding and navigation problems efficiently. - Explore meta-heuristic optimization methods including Simulated Annealing and Genetic Algorithms to find solutions for complex combinatorial challenges. - Configure Particle Swarm Optimization to simulate collective intelligence and solve continuous optimization problems. - Build game-playing engines using the Minimax algorithm enhanced by alpha-beta pruning for strategic decision-making. - Practice clean coding standards using modern Java features like records and local variable type inference to write readable algorithm implementations. The journey begins with fundamental definitions of graphs, states, and search spaces, ensuring you have a solid conceptual foundation. From there, you will progress through structured written modules, moving from basic pathfinding to advanced optimization techniques and interactive game trees. This course is designed for programmers who are new to artificial intelligence and want to understand the mechanics behind classic search and optimization algorithms. A basic familiarity with Java syntax is recommended, but no prior experience with AI or advanced mathematics is required. Start reading today to unlock the fundamental algorithms that power modern intelligent systems.