Hill Climbing Search {AI}

gfg

1. Initial State: Start with an arbitrary or random solution (initial state).
2. Neighboring States: Identify neighboring states of current solution by making small adjustments (mutations or tweaks).
3. Move to Neighbor: If one of the neighboring states offers a better solution (according to some evaluation function), move to this new state.
4. Termination: Repeat this process until no neighboring state is better than the current one. At this point, we have reached a local maximum or minimum.

# func HilLClimb(problem){  
#   current = problem.initial(random)  
#   while true:  
#      neighbor = highest_valued_successor  
#      if(value(neighbor)) \leq Value(current) return current  
#      current = neighbor  
# }