Game Theory and Greedy Algorithms for Competitive Programming

Master the foundational strategies that top competitive programmers use to solve complex algorithmic challenges efficiently. This text-based course guides you through the core concepts of mathematical game theory and greedy strategy design. You will start with the absolute basics, learning how to analyze game states and identify optimal, locally-best decisions before writing clean, efficient code. What you'll learn: - Understand foundational game theory concepts, including impartial games, Nim-sum, and the Sprague-Grundy theorem. - Implement greedy heuristics to find optimal local solutions that lead to global optimization. - Analyze time and space complexity to ensure your solutions pass strict execution limits. - Practice identifying when a greedy approach is correct versus when it fails. - Apply clean, modern programming practices using standard library data structures for efficient execution. The course begins with basic terminology and foundational mathematical definitions before moving on to step-by-step breakdowns of classic competitive programming problems. This course is designed for beginners in competitive programming; a basic understanding of any programming language is helpful but no prior advanced math or algorithms experience is required. Start reading today to sharpen your problem-solving skills and write faster, more optimal algorithms.