stockfish 10 vs. Mephisto III S Glasgow

[Madeleine Birchfield]

Just like the analogy of the GPS navigation system mentioned earlier, it's not really planning a route from point A to point B. It identifies where you are now and where you want to go then triangulates. Then with that information it looks up the route in a database. Sure it may appear to be planning but it's really not.

In computer chess, it would be an evaluation function rather than a database, and a search algorithm rather than triangulation. After all, the space of all possible games is a graph, which is also the case with navigation systems and stuff like Google maps as well where the space of all locations is modeled as a graph.

[mhull]

It seems to boil down to a human aesthetic. Do we marvel at computer games like we do the games from Morphy or Capablanca?

I think the answer has always been "yes, sometimes". Even TC must admit this as many of his own dedicated CC reviews testify. Back in the day the David Kittinger programs were admired for their natural game play. The Novag Super Constellation and Super Forte C come to mind in this regard -- the latter garnering praise, even from international masters.

Recently, the Alpha Zero project impressed top players with it's seemingly intuitive understanding of chess strategy, breathing new life into the game and delighting chess enthusiast with "beautiful games" in contrast to previous trend of incomprehensible contests between machines playing arcane and "disgusting engine lines".

So, they aren't all "bloody iron monsters".

[dkappe]

How is reinforcement training neural networks, like what Tomasz Sobczyk is doing right now for Stockfish and what Dietrich Kappe is doing for Komodo Dragon, not teaching an a chess engine how to plan? Or if reinforcement training isn't giving a chess engine knowledge, then why is Leela, which Thorsten Czub likes to claim is different from Stockfish, any different from Stockfish and not just like another pocket calculator?

The stockfish team isn’t doing Reinforcement Learning (RL). They are using leela data (which is actually RL data) with some additional self generated correction data. That’s not a criticism, just an observation. They are able to do quite a bit with filtering the data and tweaking the training software.

Dragon, though, is doing reinforcement learning, where each subsequent net generates new data and the old data drops out the back of the training window.

[mhull]

Back to the topic.
A plan is not a main line

Stockfish main line and score shows it has no plan.

One might observe that a plan is a human way of coping with his limited ability to search the tree of possibilities. Computers search rather than plan because its simpler and more natural to implement on a computer than to implement planning on a computer. And searching just works. If something works, humans are reluctant to fix it.

Not that it hasn't been tried,though:
https://www.chessprogramming.org/Paradise

Steven Edwards tried to build upon the Paradise idea, to create a program that would make plans around key features detected in a position. Somewhere along the way, the effort slowed and then stopped. AFAIK, he never talked much about why the project stalled. He continued to refine the A/B searcher function of his program Symbolic (which could play whole games in itself) but the higher level planning functions were never finished.

[mclane]

This here ?!
http://www.ai.sri.com/pubs/files/465.pdf

[mhull]

This here ?!
http://www.ai.sri.com/pubs/files/465.pdf

Affirmative. Steven Edwards' Symbolic was intended to take the Paradise concept to the next level.

[mclane]

Did it play games ?! Or was it unfinished?

[mhull]

Did it play games ?! Or was it unfinished?

Paradise was unfinished. It could solve test positions but couldn't play a full game of chess.

Symbolic could play full games using the toolkit A/B searcher. But it could not play a game using the plan-production functions which was the goal. In that sense, it too was unfinished.