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algorithms

Algorithm design and analysis skill for DSH; use when working on optimization, data structures, or computational procedures.

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Skill: Algorithms

Domain: build | Depth: axiom

Capabilities

  • Graph algorithms: shortest path, MST, centrality, community detection (networkx)
  • Sorting, searching, dynamic programming
  • Optimization: gradient descent, genetic algorithms, simulated annealing (scipy)
  • Cryptographic primitives: hashing, entropy
  • Tree structures: BST, heap, trie
  • Complexity analysis tools
  • Pathfinding: A*, Dijkstra, BFS, DFS

Libraries

LibraryPurpose
networkxGraph algorithms
scipyOptimization algorithms
numpyArray-based algorithm primitives

Module

agents/skills/algorithms.py

Key Functions

  • shortest_path(graph, src, dst) — Dijkstra shortest path
  • mst(graph) — minimum spanning tree
  • centrality(graph) — betweenness + eigenvector centrality
  • astar(grid, start, goal, heuristic) — A* pathfinding
  • genetic_optimize(fitness_fn, population, generations) — genetic algorithm
  • entropy(data) — Shannon entropy
  • topological_sort(dag) — topological ordering

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