Explore algorithms, game theory, and risk-averse decision making in this comprehensive lecture from the Real-Time Decision Making Boot Camp. Delve into real-world applications of decision-making processes, starting with an introduction to algorithms and their basics. Learn about graph theory, shortest path problems, and the Dijkstra algorithm. Examine algorithm design techniques, running time analysis, and NP-Complete problems. Discover approximation algorithms and their application to the Traveling Salesman Problem. Investigate game theory concepts, including equilibria, social optimum, and the Price of Anarchy. Gain insights into risk assessment through Expected Utility Theory, mean-variance framework, and coherent risk measures. Understand the implications of risk attitudes and the algorithmic challenges they present. Conclude with valuable algorithmic insights for tackling complex decision-making scenarios.