| name | bfs-state-space |
| description | Model minimum-move problems as BFS over a state space. Use when solving bucket pouring puzzles, sliding tiles, or any problem asking for the shortest sequence of moves to reach a goal. |
| topic | State-Space Search |
| token_cost | 120 |
| related | ["dfs-vs-bfs","dynamic-programming"] |
| keywords | ["bucket","pouring","state space","minimum moves","shortest sequence","reach goal","transitions","visited states","water","pour","fill","empty"] |
When to use
When a problem asks for the MINIMUM number of moves/steps to reach a goal state (bucket pouring, puzzle solving, sliding tiles), model it as BFS over a state space.
Rules
- State = a tuple of all values that fully describe the situation (e.g. (bucket_a, bucket_b))
- From each state, enumerate every legal transition and produce the next state
- Use a visited set keyed on the state tuple to avoid cycles
- BFS from the start state; the first time you pop a state matching the goal, its distance is the minimum move count
- Track which bucket holds the goal and the other bucket's value at that point
- NEVER skip the visited check — cycles will cause infinite loops
- ALWAYS encode forbidden moves as filters on transitions, not as special cases
Example
Transitions for bucket pouring: fill A, fill B, empty A, empty B, pour A→B, pour B→A.
Edge cases
If start_bucket is forbidden as an immediate "fill the wrong one first" move, encode that as a filter on the initial transitions.
Example
Bucket pouring: state = (a, b). Transitions: fill A, fill B, empty A, empty B, pour A→B, pour B→A. BFS from (0, 0); first time a state has a goal value, that distance is the minimum.
