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    • Episode 1 — Python and PyRat
    • Episode 2 — Manipulate the maze and graphs
    • Episode 3 — Finding a unique piece of cheese
    • Episode 4 — Shortest paths, min-heaps and algorithmic complexity
    • Episode 5 — Finding several pieces of cheese in the maze
    • Episode 6 — Heuristics, greedy approaches, accuracy/complexity trade-off
    • Episode 7 — Combinatorial game theory, winning strategies
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    • Episode 9 — Present your AI
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PyRat

PyRat

Algorithmics and Discrete Mathematics

  • Welcome
  • All episodes
    • Episode 1 — Python and PyRat
    • Episode 2 — Manipulate the maze and graphs
    • Episode 3 — Finding a unique piece of cheese
    • Episode 4 — Shortest paths, min-heaps and algorithmic complexity
    • Episode 5 — Finding several pieces of cheese in the maze
    • Episode 6 — Heuristics, greedy approaches, accuracy/complexity trade-off
    • Episode 7 — Combinatorial game theory, winning strategies
    • Episode 8 — Imagine your own AI
    • Episode 9 — Present your AI
  • The PyRat software
    • Installing it
    • How it works
  • The tournament
  • Important resources
    • Course calendar
    • Evaluation sheet
    • Google Colab
    • Mattermost
    • Moodle
    • Campus machines
  • My account

My account

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Shortcut to the articles

  • Addressing a computational problem
  • Algorithm complexity
  • Approximate solutions
  • Bruteforce and backtracking to solve NP-complete problems
  • Combinatorial game theory
  • Computing winning positions in a game
  • Dijkstra’s algorithm
  • Good programming practices
  • Graph traversal
  • Graphs and paths
  • Greedy algorithms
  • Heuristics
  • How the PyRat maze game works
  • Min-heaps
  • Present your approach and criticize its results
  • Problem complexity and NP-completeness
  • Queuing structures
  • Representing graphs
  • Routing tables
  • Statistics and plots
  • The traveling salesman problem
  • What is Python?

Shortcut to the labs

  • Lab 1 — Python reminders and PyRat installation
  • Lab 2 — Your first PyRat program
  • Lab 3 — Implement a BFS algorithm to catch a piece of cheese (in a maze without mud)
  • Lab 4 — Implement Dijkstra’s algorithm to catch a piece of cheese
  • Lab 5 — Catch all pieces of cheese in the maze
  • Lab 6 — Implement a greedy algorithm to catch all the pieces of cheese
  • Lab 7 — Design your own AI
  • Lab 8 — Design your own AI (bis)
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