im working on a minimax search tree with a depth bound...but i want to make sure i understand it first before i go ahead and implement it with this type of search, you expand the tree up to the depth bound ...say its 4, so you expand the tree 4ply, at each node should be an evulatation of the game state, and depending on what ply the bottom is for (max or mini) you choose based on that and propogate upwards to the root...or your (max) moves, correct? example: say the root is the current state, 1st ply is max''s possible board states and 2nd ply is min''s possible board states...if the depth bound is 2, youll have all of min''s possible moves...so you choose the least one and propogate upwards? what if min has more than one "worst state" which one do you choose? assuming i understand the concept correctly

Minmax

i wonder who appointed you the techie jargon police?

anyways...minimax is an also valid term for the search...my Artificial Intelligence: Structures & Strategies for Complex Problem Solving book uses the term "minimax"

and if you search for the word ''minimax'' and ''minmax'' on google you''ll find that ''minimax'' yields TWICE as much more links than ''minmax'' and that with a ''minmax'' keyword, the number 1 hit ISNT even on the topic of AI, its for mineral searching..and that google comes up with a "Did you mean minimax search??"

so id say your term is the wrong one.

aside from that ive figured out how MiniMax search ..so nm

Feeling a little insecure are we?

I posted what we internet users call a link. Maybe you should have clicked on it.

I wasn''t trying to correct you. I was giving you a link to a website that talked about minmax. I personally don''t care what you call it.

Maybe I''ll think twice before trying to give you any help next time.