[FRIAM] Google self-evolving AlphaZero artificial intelligence program mastered chess from scratch in 4 hours: Rich Murray 2017.12.10
John Kennison
JKennison at clarku.edu
Mon Dec 11 16:22:42 EST 2017
I agree that it's not clear that AlphaZero would excel at the supergame.I described. Still human intuition is probably not the indispensable ingredient that it once might have seemed to be.
On the other hand, many chess commentators think that AlphaZero has a playing style that is "more human" than the styles of other chess computers. When humans play chess, we can often discern themes --maybe one player is trying to breakthrough in the center while the other is trying to breakthrough on a flank. In contrast, most computers are simply trying to maximize a position evaluation function. This only leads to a successful breakthrough if the computer can see in advance that the breakthrough will lead, in a relatively short time, to a measurable advantage, such as the forced win of a pawn.
Humans sometimes say that they need a plan -even a bad plan is said to be better than playing without a plan. AlphaZero's games against the computer Stockfish seem to pursue clear-cut plans (at least the games that have been made available). It may be the case that having a plan leads to better play. The point is that the plan changes the evaluation function --if you want to breakthrough in the center, you try to post your pieces differently than if you are planning to breakthrough in a flank. Having a plan, even a bad plan, may lead to better coordination of your pieces --even for a computer.
Magnus Carlsen, the current human world chess champion, said that if you play against a top computer you will surely lose but you will also be bored. I think that you find a game you are watching interesting when you can sense competing plans behind the moves. AlphaZero's games are quite exciting.
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From: Friam <friam-bounces at redfish.com> on behalf of Russ Abbott <russ.abbott at gmail.com>
Sent: Monday, December 11, 2017 12:36:53 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Google self-evolving AlphaZero artificial intelligence program mastered chess from scratch in 4 hours: Rich Murray 2017.12.10
Not clear that AlphaZero would do well on John's SuperGame. It won on chess (and Go) by playing against itself in advance. If it doesn't have the opportunity to do that it won't have that advantage. It's strategy would have to be something like on-the-fly playing the selected game against itself in the background at the same time as it is playing the human opponent. The question then is how fast it can teach itself the new game. It's strategy would have to be to slow down the game against the opponent as much as possible to give itself time to learn the new game. So it becomes a matter of computer speed (for learning the new game) and the extent to which the real game can be delayed as it is in progress.
On Mon, Dec 11, 2017 at 8:58 AM Steven A Smith <sasmyth at swcp.com<mailto:sasmyth at swcp.com>> wrote:
Marcus wrote:
Is a strategy anything more than a coarse-grained tactic? And is intuition anything more than an associative memory that connects coarse- and fine- grained information?
Is it any more? Or any less?
Learning is an iterated game that operates at many scales and on many dimensions...
<TL;Don'tRead>
The Biological Evolution record shows myriad explosions in quantity and diversity that resulted from a (small? but) significant innovation (e.g. multicellular organisms, Eukaryotes, photosynthesis, oxygen metabolisms, vertebrae, warm blooded metabolism, live birth, etc). Punctuated equilibrium?
There seem to be similar inflection points in the "learning" implied in human social/technological/economic evolution and we may be in on the shoulder of "yet another" which gestures in the direction of the von Nuemann/Vinge/Kurzweillian "technological singularity".
I'm not much of a chess expert, myself, playing only *barely* competitively in my late teens (as Spassky and Fischer were dukingit out), and revisiting it in the pre-ALife era of "evolution, games, and learning" in the late 80s, along with GO. Chess itself, as a "playing field" for learning strategy is a microcosm to observe the general idea of "learning". The history of chess is fascinating. In the current context, it is fascinating that out of about 1500 years of existence (in proto-forms), for a little over 500 of it, the rules have settled on what we use today, but the tactics and strategies developed *on top* of those has continued to both *evolve* and *reflect* society at large. Most notably, perhaps, the "Romantic Period" where one of the dominant ideas was that personal genius *and* style mattered more than theory or logic or even board positions. This somewhat reflected the military and political style of that period. During the "age of Enlightenment" it also had a moral embedding... The "modern" era emerged with the industrial revolution and more importantly perhaps, the mechanization of war where chess strategy, now somewhat more "scientific" began to eventually give rise to "hypermodernism" which focus more on controlling the center of the board from afar (a parallel to mechanized warfare where power could be projected over a great distance in a short amount of time). Algorithmic play and mathematical analysis has been considered since the late Romanitc period but didn't come into it's own until the modern digital computer, with Claude Shannon taking an early swipe at the problem as early as 1950! The fact that it took more than 50 years to get to Deep Blue's thin victory over Kasparov is more a testimony to how subtle and hard Chess is than how intelligent humans are, etc.
"Deep Learning" itself seems like nothing more (and nothing less) than the latest innovation in machine learning (game theory, neural nets, cellular automata, genetic algorithms, learning classifiers, etc.) which *could* very well portend the breakaway point of the AI-driven technological singularity. I'm not THAT up on "Deep Learning" but things like Generative Antagonistic Networks (and other unsupervised machine learning) seem to have the key quality of not needing supervision by humans to learn... there may be one more level of indirection to be had before things go ape-shit (exponentially speaking)...
I personally don't imagine that a *single* AI will be the source of this, but rather a Cambrian-explosion-like plethora of AI's, though they may be so pervasive and promiscuous as to cross-fertilize so thoroughly that they will be a single "organism" for all practical purposes.
</TL;DR>
- Steve
From: Friam [mailto:friam-bounces at redfish.com] On Behalf Of John Kennison
Sent: Monday, December 11, 2017 7:17 AM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com><mailto:friam at redfish.com>
Subject: Re: [FRIAM] Google self-evolving AlphaZero artificial intelligence program mastered chess from scratch in 4 hours: Rich Murray 2017.12.10
I once thought I had a sure-fire way to make games between humans and computers fairer. Start with a large set of chess-like games that use different boards, different pieces, different rules. Enumerate the games so that each one corresponds to a n-digit binary numeral (for large n). Then make a "super game" in which the players start by creating a n digit binary numeral by taking turns in which they can specify one of the n binary digits. The super game would continue by playing the chess-like game that corresponds to the created number.
In a super game between a human and a computer, the computer would not have access to all the insights into the nature of chess that humans have established over hundreds of years of playing chess and which chess playing computers use to defeat humans. Of course, the human player would also be deprived of all the years of research into chess, but humans can use their marvelous intuition to figure out a reasonable set of strategies even for a game they haven't studied before. The computer, without a reasonable set of strategies, would (I assumed) find little benefit from its massive computing power.
The new AlphaZero game playing computer refutes my idea.
________________________________
From: Friam <friam-bounces at redfish.com<mailto:friam-bounces at redfish.com>> on behalf of Rich Murray <rmforall at gmail.com<mailto:rmforall at gmail.com>>
Sent: Monday, December 11, 2017 12:16:26 AM
To: Rich Murray
Subject: [FRIAM] Google self-evolving AlphaZero artificial intelligence program mastered chess from scratch in 4 hours: Rich Murray 2017.12.10
https://futurism.com/4-hours-googles-ai-mastered-chess-knowledge-history/
Chess isn’t an easy game, by human standards. But for an artificial intelligence powered by a formidable, almost alien mindset, the trivial diversion can be mastered in a few spare hours.
In a new paper, Google researchers detail how their latest AI evolution, AlphaZero, developed “superhuman performance” in chess, taking just four hours to learn the rules before obliterating the world champion chess program, Stockfish.
In other words, all of humanity’s chess knowledge – and beyond – was absorbed and surpassed by an AI in about as long as it takes to drive from New York City to Washington, DC.
After being programmed with only the rules of chess (no strategies), in just four hours AlphaZero had mastered the game to the extent it was able to best the highest-rated chess-playing program Stockfish.
In a series of 100 games against Stockfish, AlphaZero won 25 games while playing as white (with first mover advantage), and picked up three games playing as black.
The rest of the contests were draws, with Stockfish recording no wins and AlphaZero no losses.
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--
Russ Abbott
Professor, Computer Science
California State University, Los Angeles
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