Graph Theory
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## TL;DR Graph theory studies networks of vertices connected by edges. Applications: social networks, routing algorithms, dependency resolution, compiler optimization (register allocation via graph coloring), circuit design. Euler's 1736 Bridges of Konigsberg paper founded the field. ## Core Explanation Directed vs. undirected. Weighted graphs model distances/costs. Complete graph K_n: every vertex connected to every other. Bipartite graph: vertices can be partitioned into two independent sets. Planar graph: can be drawn without edge crossings (Euler's formula: V - E + F = 2). Trees are connected acyclic graphs. Spanning trees connect all vertices with minimum edges. ## Further Reading - ## Related Articles - [AI for Complex Networks: Graph Learning, Resilience, and Network Science](../../ai/ai-for-complex-networks.md) - [AI for Fraud Detection: Graph Neural Networks, Anti-Money Laundering, and Financial Crime](../../ai/ai-for-fraud-detection.md) - [AI for Game Theory: Computational Game Playing, Nash Equilibrium, and Multi-Agent Strategy](../../ai/ai-for-gaming-theory.md)