Announcing the Algorithms Category

The Algorithms & AI category has been live for a while, but it now has its own dedicated landing page with category-specific accent colours, featured simulations and article links. Here's what's in it.

What's in the Category

🗺️ A* Pathfinding Live maze grid — watch A* find the shortest path in real time 📊 Sorting Visualiser Quicksort, mergesort, heapsort — colour bars animated step by step 🌀 Maze Generators DFS, Prim's, Wilson's — structured random labyrinths generated on the fly 🧬 Genetic Algorithm Watch a population evolve to solve the Travelling Salesman Problem 🧠 Neural Network A 3-layer MLP learns XOR in real time — no libraries, pure JS 🗺️ TSP (Travelling Salesman) Nearest neighbour + 2-opt heuristics animated across random city maps

Why Algorithms?

Algorithms are often taught with static diagrams or pseudocode. But they're processes — they have dynamics, they make decisions, they explore spaces. Animating them in real time reveals things that a flowchart never could: why A* finds the shortest path without exploring the whole grid, why genetic algorithms converge to local optima, why quicksort degrades on already-sorted input.

Every simulation in this category lets you interact with the algorithm while it runs. Change the maze walls, disturb the swarm, adjust mutation rates — see the effect immediately.

Coming Up

In the pipeline: a full graph algorithm explorer (BFS, DFS, Dijkstra, Bellman-Ford), an ACO-driven TSP solver, and a reinforcement learning demo where an agent learns to navigate a grid world. Watch this space.