[Computer-go] AlphaGo Zero SGF - Free Use or Copyright?
sheppardco at aol.com
Thu Oct 26 04:52:51 PDT 2017
Robert is right, but Robert seems to think this hasn't been done. Actually every prominent non-neural MCTS program since Mogo has been based on the exact design that Robert describes. The best of them achieve somewhat greater strength than Robert expects.
MCTS is the glue that binds incompatible rules. It rationalizes different heuristics into a coherent whole by testing the ideas in a competition against one another using a meaningful evaluation (win/loss).
From: Computer-go [mailto:computer-go-bounces at computer-go.org] On Behalf Of Xavier Combelle
Sent: Thursday, October 26, 2017 1:50 AM
To: computer-go at computer-go.org
Subject: Re: [Computer-go] AlphaGo Zero SGF - Free Use or Copyright?
>> The reason why (b) had became unpopular is because there is no go
>> theory precise enough to implement it as an algorithm
> There is quite some theory of the 95% principle kind which might be
> implemented as approximation. E.g. "Usually, defend your weak
> important group." can be approximated by approximating "group",
> "important" (its loss is too large in a quick positional judgement),
> "weak" (can be killed in two successive moves), "defend" (after the
> move, cannot be killed in two successive moves), "usually" (always,
> unless there are several such groups and some must be chosen, say,
> randomly; the approximation being that the alternative strategy of
> large scale exchange is discarded).
> Besides, one must prioritise principles to solve conflicting
> principles by a higher order principle.
> IMO, such an expert system combined with tree reading and maybe MCTS
> to emulate reading used when a principle depends on reading can, with
> an effort of a few manyears of implementation, already achieve amateur
> mid dan. Not high dan yet because high dans can choose advanced
> strategies, such as global exchange, and there are no good enough
> principles for that yet, which would also consider necessary side
> conditions related to influence, aji etc. I need to work out such
> principles during the following years. Currently, the state is that
> weaker principles have identified the major topics (influence, aji
> etc.) to be considered in fights but they must be refined to create
> 95%+ principles.
> In the 80s and 90s, expert systems failed to do better than ca. 5 kyu
> because principles were only marginally better than 50%. Today, (my)
> average principles discard the weaker, 50% principles and are ca. 75%.
> Tomorrow, the 75% principles can be discarded for an average of 95%
> principles. Expert systems get their chance again! Their major
> disadvantage remains: great manpower is required for implementation.
> The advantage is semantical understanding.
>From a software developer point of view enlighten by my knowledge of history of ai and history of go development,
such approximate definition is close to useless to build a software at the current state of art.
One of the reason is as you state the considerable work it would require to implement a huge number of imprecise rules.
As you are not a software developer, I want you to look on this comics which state the difference between apparent difficulty and real difficulty of developping software. https://xkcd.com/1425/ As far as I understand your task to implement such an expert system would require the many years of implementations would be thousands of years.
As far as my experience speak the expected reward would be a win of one or two rank and so definitely not a mid dan amateur level.
Computer-go mailing list
Computer-go at computer-go.org
More information about the Computer-go