Decision Making in Dynamic Environments: Foundations of Multi-Agent Systems

Making decisions in unpredictable, rapidly changing environments is one of the most critical challenges in modern systems and artificial intelligence. This course provides a clear, step-by-step introduction to the core principles of dynamic decision-making and multi-agent interactions, helping you understand how autonomous agents negotiate, compete, and cooperate. What you'll learn: • Understand foundational terminology of dynamic environments and agent-based systems • Explore how intelligent agents model uncertainty and evaluate strategic choices • Analyze multi-agent interactions, including cooperative and competitive scenarios • Discover modern decision patterns, including basic reinforcement learning concepts and heuristic search • Apply decision-making frameworks to real-world scenarios through structured written exercises. Starting with basic definitions, you will progress through strategic models and interaction protocols, building a solid conceptual foundation. This course is designed for absolute beginners interested in systems design, game theory, or artificial intelligence, requiring no prior technical background. Start reading today to build your understanding of intelligent, adaptive systems.