Demo 01
Symbolic AI And Search: Can machines act intelligent by searching?
Early AI treated intelligence as finding answers in spaces with explicit rules. This chapter shows why search is powerful and why it encounters combinatorial explosion as the state space grows.
Teaching interaction
Symbolic AI And Search: Can machines act intelligent by searching?
Why did early AI rely on search, and why did it encounter combinatorial explosion?
BFS expands every possibility level by level
Breadth-first search does not guess a direction immediately. It expands one level at a time, which is reliable but quickly creates many states.
- Understand how search can systematically find solutions in a space with explicit rules.
- Compare BFS, DFS, and A* by expansion order and frontier cost.
- See why combinatorial explosion appears as the state space grows.
This demo uses a small preset search tree and does not run a real A* algorithm. Node order and costs illustrate differences between search strategies.
Observation guide
Search excels with explicit rules but fears state growth
The earlier problem was that machines still lacked an executable method for problem solving. Search addressed path finding and planning, but it did not solve knowledge representation, heuristic quality, or explosive scale. Its follow-on influence includes planning, game trees, A*, and search ideas in reinforcement learning.
References