on the subject of brutish intelligence, here is a sneak preview of a draft of the script for episode 4 in the series:
HALy is an imaginary robot, named after two famous computers: HAL, the antihero of Arthur C. Clarke's wonderful movie 2001: A Space Odyssey, and Haylee, the hero and Secretary General of the International Go Federation. Whereas HAL was made of electronics, Haylee is a real person made of flesh and bone. I'm not being rude to call Haylee a computer, because all human beings - and indeed, all living things, from blue whales to underwater photographers, including you and me and even the bacteria in our guts - are computers. Living computers. Every cell in your body is a miniature computer, made out of what Dennis Bray calls wetware, because the computational machinery of life, made of living plastics like proteins and other stuff, lives in the watery insides of biological cells. HALy's logic is based on what Haylee tells us about when she is playing Go. HAly tries to imagine in it's own head the mental images that Haylee talks about when she is playing. It does this by expressing Haylee's commentaries in the form of symbolic rules; rules that one day a clever computer programmer might be able to turn into computer software so HALy could take the big step from fiction to fact. Let's look at some of Haly's rules: oh, by the way, if HALy were ever able to play a whole game of Go, it would need thousands, possibly millions of rules, but so far i've only thought of a few of them. Here's one, derived from Haylee's explanations in the previous episode of this series: IF i want to play in an empty corner AND opp has some strong stones facing the empty corner on one of the sides next to it THEN look for a joseki that won't give opp a complementary position between its outcome and what he has already on that side This rule is a generalisation of the example Haylee talked about. In that example, she was thinking of where to play in the lower left corner, whilst the lower right corner was occupied by a single opp stone on the hoshi point. HALy can see straightaway whether a corner is empty or not, but how about some of the other qualities in the rule? Like "strong", "facing" and "complementary"? These need to be worked out; to be thought through. "facing" is the simplest quality to determine - to keep the explanation simple, let's pretend we are white and opp is black. If the nearest stone along the side is black, it's facing us. Here are some examples of groups that face towards the lower left And some examples of groups that dont. This one doesn't either, but you would hardly call the black stone strong, as it is overshadowed and will have a hard time living. Remember, the rule only applies to strong stones facing the empty corner. So we need to find a way to work out whether stones are strong or not. And right away we are plunged into the forest of complexity, because whether or not a stone is strong depends on whether or not it will live. Tsume-go at the very beginning of fuseki!! How to solve a tricky problem? There are basically two approaches: you can either work hard, or work smart. In Go, "working hard" means reading it all out - or as much of it as you can. It's the basic strategy used by Monte Carlo search, which operates a bit like a whilrling dervish, flailing around in all directions and relying on a relatively simplstic evaluation function that can at least identify big swings at the end of long sequences, and a prodigious mental energy to read out millions of such sequences. It's a kind of brute force search, which although not exhaustive, is extensive enough to make it hard for its opp to predict what it's going to do next. Monte Carlo players often make bizarre moves that are strikingly dumb but occasionally impressively tricky. The technique has taken the best of them high up in the amateur ranks, far higher than i imagined possible 40 years ago, serving to demonstrate yet again that most of us mere mortals are not as smart as we fondly like to imagine we are! In contrast, "working smart" means standing on the shoulders of the armies of great players who have gone before you, and by trial and error over the centuries, worked out some general principles that usually work. AI people call such principles "heuristics", a Greek word meaning "rule of thumb". We use heuristics in our daily lives all the time; and it is possible that using heuristics is the very essence of intelligence. For example, one heuristic used by magicians, footballers, fencers, rugby players, and kangaroos, is the feint. The feint is a brief movement in one direction, immediately followed by a sharp turn and a dodge in the other direction, in order to avoid an onrushing predator. It works because the attacker (or audience member of a magic show) has a brain which, like the brain of the common housefly, is programmed to detect movement and to imagine, as stock market players all too often imagine, that is something starts going in one direction, it will continue to go on in that same direction. This is the simplest kind of mathematical reasoning, called linear extrapolation. Christiano Ronaldo and Lionel Messi are modern masters of the feint on the football field, who learned their dancing skills by following in the footsteps of great dribblers of the past like George Best and Zinedine Zidane. Kangaroos are masters of the feint too, which presumably they learned through evolution to escape dingo attacks. Unfortunately for the kangaroos, there is an new animal on the block that is much more dangerous to them than the dingo. It's the motor car. Motor car drivers don't have brains like dingos, so they swerve to avoid a kangaroo that hops into the road (or is sleeping on it because the road is a touch warmer than the soil of the desert). The motor car driver swerves in the opposite direction to the kangaroos feint, thereby crashing into it as the kangaroo abruptly changes direction, right into the path of the swerving car. So the best way to avoid hitting a kangaroo on the road at night is to aim straight at it, and it will dodge out of your way. The feint is often useful in Go too, in the form of a sacrifice move, which attracts the attention of the opponent, and whilst he is busy capturing it, you can build strength in the other direction for use later on. The crosscut is an example of the feint, which encourages the opp to busy himself on one side whilst you build some shape on the other side, making it a useful tactic for invading a moyo. HALy's basic strategy is KISS, which stands for Keep It Simple, Stupid! ....more to come On 4 August 2015 at 10:33, djhbrown . <djhbr...@gmail.com> wrote: > Thanks for the link to the CMU CNN paper, Steven, which was very > interesting. I noted with some pleasure that they included a fovea stream > - although maybe that is a bit of a misnomer, as whereas animal foveas roam > around the image, building (i think) a symbolic structural description of > the picture, theirs was fixed in the middle. > > I wonder whether a roaming fovea CNN could be a successful "group > connectedness" classifier? I can envisage the fovea being moved around by > a higher-level routine that uses a symbolic description of the game > situation to identify which areas/groups it wants it to investigate. > > Incidentally, i'm unconvinced that including an age of stone feature is > valuable, because although the future is dynamic, the past is set in stone > (sic); Go teachers sometimes talk about tewari analysis to demonstrate > when an old stone becomes inefficiently placed by a certain line of play. > > As to romantic notions of human superiority, i personally feel that such > opinions are not so much romantic as hubristic - or perhaps paranoid! > However, i have to admit that in 1979 i was a false prophet when i claimed > "the brute-force approach is a no-hoper for Go, even if computers become a > hundred times more powerful than they are now" [Brown, D and S. Dowsey, > S. The Challenge of Go. *New Scientist* 81, 303-305, 1979.]. Back in > those days, i never imagined that something so blind as Monte-Carlo would > become more perceptive than even my weak eye, let alone being able to > defeat a pro (albeit with a 5-stone handicap), as Zen just did on KGS. > > By the way, i've long since lost my paper copy of my paper; you have > access to an academic library - would you be able to retrieve and scan a > copy of it, just for my nostalgia? > > > > -- > personal website <http://sites.google.com/site/djhbrown2/home> > > > > > > > -- personal website <http://sites.google.com/site/djhbrown2/home>
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