I think it's actually quite fast for a plain-alpha beta, assuming you're talking about the initial position. More importantly, does the search return a move you're expecting?

This is chess programming. Chess programming is actually very simple if you knew whether an algorithm would work without spending hours on testing. It takes more than simply speed vs accuracy, it's much harder than that. You need to devise a way to achieve good speed while searching for nodes that ...

I posted the question because I also read the page. I'm looking for an understanding why exactly this is a lower bound. Say, if alpha = 1, beta = 5, our evaluation gives 10. We fail high, and return 10. At the end of the search, considering all possibilities, the PV line gives a score of 3. Shouldn ...

Why in a fail-high framework, the returned score is a lower bound? I'd expect if score >= beta, and we return score. The score would be an upper bound to the exact score.

Thanks. Sorry I was away. Thanks for the copies!

Thanks Bob! I'll send you an email to your university account on Tuesday. ^^

Anyway to access an old paper from 1993?

Null Move and Deep Search: Selective-Search Heuristics for Obtuse Chess Programs

Their website only has a table of contents for this old paper.

I can see that qsearch() does the evaluation as expected. But my concern is in the main search function defined by

Value search(Position& pos, Stack* ss, Value alpha, Value beta, Depth depth, bool cutNode)

When I was reading the function, I see in step 5

// Step 5. Evaluate the position ...

Isn't chess engine a deep-first search? In search.cpp in Stockfish, we have:

eval = ss->staticEval = evaluate(pos);
TT.store(posKey, VALUE_NONE, BOUND_NONE, DEPTH_NONE, MOVE_NONE, ss->staticEval);

This is not done at the leaf, but I've seen in other engines we only evaluate a position at the ...