Java AI Foundations: Search Algorithms and Robot Path Planning

Adding intelligent decision-making and automation to your software is one of the most valuable skills you can develop as a programmer. Understanding how AI algorithms work under the hood allows you to solve complex routing, automation, and optimization problems from scratch. This text-based course guides you through the foundational concepts of Artificial Intelligence, focusing on search algorithms and robot path planning in Java. You will transition from understanding basic AI theory to writing clean, efficient Java code that simulates pathfinding and intelligent decision-making. What you'll learn: - Understand the core history, classifications, and fundamental definitions of Artificial Intelligence. - Differentiate between uninformed search and informed search strategies for problem-solving. - Implement classic search algorithms in Java, including Breadth-First Search (BFS) and Depth-First Search (DFS). - Model complex pathfinding environments and map states using modern Java features like Records. - Apply search techniques to solve practical robot path planning and grid-navigation problems. - Analyze algorithm performance and efficiency to choose the right search strategy for different scenarios. You will start by exploring the core definitions and historical context of AI before diving into the mechanics of state space search. Through clear written explanations and step-by-step code implementations, you will build a solid foundation in algorithmic problem-solving. This course is designed for beginner to intermediate Java developers who want to learn how AI works under the hood without relying on complex external libraries. A basic familiarity with Java syntax is recommended, but no prior AI experience is required. Start reading today to build your foundational AI programming skills from the ground up.