Created new component and refactored

- Created new component to display the game of life algo
- created an algo info component to combine the algo header for all algos

src/assets/i18n/en.json

@@ -313,7 +313,6 @@
       "TITLE": "Algorithms",
       "DIJKSTRA_EXPLANATION": " is guaranteed to find the shortest path if all edge costs are non-negative. Advantage: optimal and without heuristics. Disadvantage: often visits a large number of nodes (can be slower for large grids).",
       "ASTAR_EXPLANATION": " extends Dijkstra with a heuristic (e.g. Manhattan distance) and can therefore search in a much more targeted manner. Advantage: often significantly faster with good heuristics; with permissible heuristics, the path remains optimal. Disadvantage: highly dependent on heuristics (poor heuristics ≈ Dijkstra).",
-      "NOTE": "Note",
       "DISCLAIMER": "This A* implementation is deliberately kept simple. It only moves in four directions and each step costs 1. The heuristic is minimal and only serves to demonstrate the principle of A* compared to Dijkstra. The goal is not an optimal or production-ready A* algorithm, but a clear visualisation of how heuristics can speed up the search."
     },
     "ALERT": {
@@ -335,7 +334,6 @@
       "BUBBLE_SORT_EXPLANATION": "repeatedly compares adjacent elements and swaps them if they are in the wrong order. The largest element \"bubbles\" to the end of the list like an air bubble. Advantage: Extremely simple to understand and implement; detects already sorted lists very quickly. Disadvantage: Very inefficient for large lists (runtime O(n²)). Rarely used in practice.",
       "QUICK_SORT_EXPLANATION": "follows the \"divide and conquer\" principle. A \"pivot\" element is selected, and the array is divided into two halves: elements smaller than the pivot and elements larger than the pivot. Advantage: On average one of the fastest sorting algorithms (O(n log n)); requires no additional memory (in-place). Disadvantage: Slow in the worst case (O(n²)) if the pivot is chosen poorly. Is not stable (changes order of equal elements).",
       "HEAP_SORT_EXPLANATION": "organizes the data initially into a special tree structure (Binary Heap). The largest element (the root) is extracted and sorted to the end, then the tree is repaired. Advantage: Guarantees a fast runtime of O(n log n), even in the worst case. Requires almost no additional memory. Disadvantage: Often slightly slower than Quick Sort in practice because the jumps in memory (heap structure) utilize the CPU cache less effectively.",
-      "NOTE": "NOTE",
       "DISCLAIMER": "The choice of the \"best\" sorting algorithm depends heavily on the data and the constraints. In computer science, three scenarios are often considered:",
       "DISCLAIMER_1": "Best Case: The data is already nearly sorted (Bubble Sort shines here, for example).",
       "DISCLAIMER_2": "Average Case: The statistical norm.",
@@ -343,6 +341,9 @@
       "DISCLAIMER_4": "Additionally, there is almost always a Time-Space Trade-off: Algorithms that are extremely fast (like Merge Sort) often require a lot of additional working memory. Algorithms that work directly in existing memory (like Heap Sort) save space but are sometimes more complex or slightly slower. Thus, there is no \"one-size-fits-all\" solution."
     }
   },
+  "GOL": {
+    "TITLE": "Conway's Game of Life"
+  },
   "ALGORITHM": {
     "TITLE": "Algorithms",
     "PATHFINDING": {
@@ -352,6 +353,11 @@
     "SORTING": {
       "TITLE": "Sorting",
       "DESCRIPTION": "Visualizing various sorting algorithms."
-    }
+    },
+    "GOL": {
+      "TITLE:": "Conway's Game of Life",
+      "DESCRIPTION": "The Game of Life is a cellular automaton devised by the British mathematician John Horton Conway in 1970."
+    },
+    "NOTE": "Note"
   }
 }