I don't know what kind of life you lead Mike, but it certainly very different from mine, in terms that I rarely find myself in very new locations.
In order for me to get from point A to point B, in an area I haven't been before, I typically collect lots of information beforehand, like getting the address, getting maps, estimating times, things like that. If I'm at someone's house, I can't just "go to the bathroom", as most of the time, I have no idea where it is, typically I have to ask where the bathroom is, and only after I'm told it's location, which usually has some intrinsic routing information i.e. "down the stairs to the left", I follow the instructions until I either find the bathroom, or get more information about how to locate it. Anyways, also going to new places really is an exotic thing, for most people that is, perhaps you're wired differently, and so wake up in a new bed every day, at some new persons house, I don't know. I've heard of some people which "couch surf" though personally I have a much more stable living situation. Also "the kitchen" is rarely a place you'd go, in anyones house, unless they were family, or very close friends, in which case it would be the same as the bathroom, information about it's location would have to be found out, before actually getting there. If for instance we were in some abandoned home, where there were no informants, then there would be the initial exploration, where each of the navigable places would be explored in turn and categorized based on their contents. If they have a toilet and bath, they are a bathroom. If they have a stove and sink they are a kitchen, if they have a bed they are a bedroom, that kinda thing. These are all stories of life which are readily describable and thereby programmable. On Sun, Dec 16, 2012 at 3:54 PM, Mike Tintner <[email protected]>wrote: > No, Logan, “go to the kitchen” is NOT to a previously known location. > > The whole point of the Woz test is that the robot must be able to “go to > the kitchen” as any human does – i.e. to ANY kitchen in ANY house – i.e. > to UNFAMILIAR/UNKNOWN LOCATIONS. No matter what the house you will be able > to go to the kitchen sight unseen And so essentially will any animal – in > the sense that you can set an animal to go down any hitherto unknown field > or street, and it will make its way down that street round whatever > obstacles there are – OR presumably if the animal can smell delectable food > from a distant kitchen, it will be able to make its way there through > whatever house. > > This is what real AGI’s do, this is what narrow AI robots/algos can’t. > Living creatures are continually exploring the world, continually going > down new paths, into new fields – and doing so in every sense of the terms, > at every level of functioning. > > You clearly think – like pretty everyone else here – that creativity and > exploration – going to an unknown location through an unknown field – are > pretty exotic. (That’s the effect of narrow AI training) Actually every > single real world activity, physical or mental, is creative/exploratory. > Going to the toilet is exploratory – you never know what you’ll find there, > especially if it’s a new Japanese toilet, – and you may have to find a new > way of coping. Reading a text is creative/exploratory because no normal > text is formulaically, predictably like any other text – every text > presents something new and you may have to find a new way of interpreting > it. Ditto any conversation. Ditto writing and reading posts here. > > The ordinary person, of course, takes all these things for granted - > thinks of them as “routine”, potentially algorithmic – but AGI-ers should > know better. > > Real world life/AGI is continuous journeys into more or less new, unknown > territories. > > > > > *From:* Logan Streondj <[email protected]> > *Sent:* Sunday, December 16, 2012 7:37 PM > *To:* AGI <[email protected]> > *Subject:* Re: [agi] Internal Representation > > to be fair the original question was about "going to the kitchen" where > word "the" means it's a previously known location. > I'm assuming that was answered to your satisfaction. > > > So now you are asking a new question, about how exploration is to occur. > Exploration is typically a goal oriented behavior, even if simply to > satisfy desire to have new experience. > > For instance a little bunny may leave the nest for a tiny hop around at > first, and then extend it's hops incrementally outside. > Once they have matured enough to be independent, they may co-locate in the > territory if there are enough resources, or find themselves a new > territory. > Typically a territory must have a source of water, food, place to make > nest or burrow and mating prospects. > > Most of an animals life is spent within it's own territory as long as all > the requirements are met. In some species, either the male or female roams > to other territories during mating season. > Also there are nomadic species, which have multiple grazing areas which > they travel between throughout the year. > > Anyways so the actual exploration is as simple as enabling a locomotion > driver into a direction, typically instincts even in babies have some > preventative measures such as avoiding going in directions with large > drops, and avoiding walking into walls. > > If there are specific goals in mind, such as for instance water, then can > pattern match to find a good location, such as a lower location, with > denser vegetation, and higher humidity. > > > > > On Sun, Dec 16, 2012 at 2:12 PM, Mike Tintner <[email protected]>wrote: > >> Logan, >> >> Yes, as I said, I could see you have a loose sense of what is needed >> (any sense can only be “loose”). >> >> However, your idea that your robot can do this by an algorithm is >> parallel with Jim’s that complexity is involved. >> >> You can only have an algo for a journey if you have already made the >> journey, and can predict the territory, – and have a route[s]-map. (That >> incl. “ replotting alternative ways of getting there” after meeting >> unforeseen obstacles). By extension, you can only have problems of >> complexity if you already have a known set of possible journeys/route-maps >> to consider (a la Travelling Salesman Problem).. >> >> That’s why algos only work in artificial controlled environments like >> factories, labs and warehouses, which are fully known and have been >> artificially structured to be predictable.. >> >> To be able to travel in the real world, is to travel through >> *unpredictable* and *more or less unknown” territories. We want robots >> which like living creatures can “go through that field” or street or room >> *blind* - just like you - through an “unstructured field” with “unknown >> obstacles” - i.e. without ever having seen it before, or encountered >> anything quite like it, or having any route-map. They will have a rough >> idea of what such travel may involve – know some of the steps that may be >> needed to go through a room – but have only partial knowledge of what is >> needed. The journey can’t be algorithmically plotted in advance – it can >> only be made up as you go along, and usually requires some innovation – >> experimenting with the body to take some new or different kinds of steps. >> >> Narrow AI/algos are for rational problems, when you already know the >> way[s] to the solution and the goal – already have the route-map. AGI is >> about creative problems when you don’t know the way[s], don’t have a route >> map – and have to make it up as you go along. All creative problems >> whatsoever are like this. >> >> If you think different, try it. What’s the algo for going through “that >> room”? Oh no, you don’t get to know what the room is in advance. You have >> to write your algo [sight of room unseen] in advance.Try it. And only then >> will I tell you what the room is and what’s in it. ... >> >> You can’t plan for the real world. You’ve got to “take it as it comes.” >> >> *From:* Logan Streondj <[email protected]> >> *Sent:* Sunday, December 16, 2012 6:04 PM >> *To:* AGI <[email protected]> >> *Subject:* Re: [agi] Internal Representation >> >> In terms of actual movement, that is done quite similarly, >> to how we have an interpreter with input and output on a screen, >> simply the outputs go to motors, and inputs are sensors. >> >> For the actual "drivers" I was intending to have the AI algorithms >> available in HSPL by that point, so that the GI could evolve drivers to >> work with the hardware it has available, and potentially work around >> hardware failures. >> >> So crawling would be defined as a form of locomotion using arms and legs >> with torso parallel to the floor. Based on a similarly simple >> description, it could then evolve a process involving the sensors and >> actuators it has available. Similar to snake robots it would be able to >> adapt to changes in it's configuration, and layout of objects. >> >> In terms of "fluidity" that is part of the process, as the course itself >> is simply a rough outline of the journey, the walking algorithm would >> evolve to take into account obstacles and such as part of the evolution of >> the walking driver. >> >> If for instance there is some unforseen obstacle, the plot could be >> replotted, for alternative potential ways of getting there. This is >> exactly how humans, do it, likely most animals as well, for instance they >> figure out where they are going to jump before jumping there. >> And if they are going to get water, they figure out a good path to take >> to get there, before actually setting out. >> >> >> >> >> On Sun, Dec 16, 2012 at 12:43 PM, Mike Tintner >> <[email protected]>wrote: >> >>> PM: You must say why it cannot be done to be helpful, which you >>> haven't. >>> >>> I would have thought a man with your imagination wouldn’t need to be >>> told – the principal reason you cannot have a complex set here, is that >>> you cannot define or calculate a) the trajectories or lines of action a >>> body must take to “go across a room”” – esp. given b) the infinite >>> diversity of starting points and positions of the body, and c) the infinite >>> diversity of obstacles that may lie in the way, and d) the infinite natures >>> and configurations of room terrains, and e) the endless combinations of >>> limbs and body positions that may be necessary to move from the infinite >>> diversity of starting points. >>> >>> The solution lies in the direction of having truly “fluid concepts” of >>> lines of action, with which the body can be fluidly aligned, and proceeding >>> not by prior consideration of a set of trajectories (which is absolutely >>> impossible) but adventurously “putting your best foot forward” towards the >>> goal, one step at a time, and seeing what happens. >>> >>> Logan’s formulations lie intuitively in that direction – but they look >>> like purely symboiic formulations – whereas internal representations must >>> be literally linear in nature. Concepts provide literally “lines of >>> action” - and involve literally “thinking along these lines”. >>> >>> >>> *From:* Piaget Modeler <[email protected]> >>> *Sent:* Sunday, December 16, 2012 4:54 PM >>> *To:* AGI <[email protected]> >>> *Subject:* RE: [agi] Internal Representation >>> >>> >>> According to Confucius, Mike Tinter, you are correct. >>> >>> "The person who says it can't be done, and the person who says it can be >>> done are both usually correct." ~ Confucius. >>> >>> If you want to use some imagination, and figure out how it can be done, >>> then by all means. If you just want to nay say >>> and say it can't be done, then that's not helpful. You must say why it >>> cannot be done to be helpful, which you haven't. >>> >>> I think it is already being done, and you simply may not know about it, >>> because certain people aren't revealing their >>> results just yet. >>> >>> ~PM. >>> >>> ------------------------------ >>> From: [email protected] >>> To: [email protected] >>> Subject: Re: [agi] Internal Representation >>> Date: Sun, 16 Dec 2012 16:06:49 +0000 >>> >>> “Complexity” is a substitute for thought here. You couldn’t begin to >>> specify what are the complex elements here. >>> >>> The reality is that living systems can translate these desires/goals, >>> however internally represented, into initial actions in a second, and >>> extended courses of action in just a few seconds. >>> >>> The idea that there is some systematic consideration of sets of sets of >>> alternative courses of action and environments – “sets of sets” because >>> the infant/animal could be in an infinite diversity of situations – is >>> quite, quite mad, i.e. divorced from any reality whatsoever other than >>> narrow AI programs which are incapable of this kind of intelligence and >>> action. >>> >>> *From:* Jim Bromer <[email protected]> >>> *Sent:* Sunday, December 16, 2012 3:09 PM >>> *To:* AGI <[email protected]> >>> *Subject:* Re: [agi] Internal Representation >>> >>> On Sun, Dec 16, 2012 at 4:43 AM, Mike Tintner <[email protected] >>> > wrote: >>> How do the words translate into a physical course of action? >>> >>> How do you get from “go” to its first and subsequent movements of limbs? >>> Bear in mind, that the same wish – the same formulation – could apply to >>> the infant in vastly diverse physical situations - initial physical >>> positions llike lying, sitting, lying on side, standing against some object >>> etc - and vastly different room configurations. >>> ---------------------------- >>> >>> There is a problem here, but the only true problem is one of >>> complexity. The same problem occurs when the program tries to make sense >>> out of the IO data that is input to the program so that it can recognize >>> what kind of situation that it is in or responding to. The problem also >>> occurs when it has to select the best kind of reaction to the situation >>> when there are many otions that it can select from which are related to the >>> complexities of the situation. There are no serious problems with >>> implementing general AI other then the complexity of these kinds of >>> problems. A situation can be recognized based on many components and there >>> are many 'ideas' (about different kinds of situations) that can be >>> recognized based on some of the components that may occur in the >>> situation. It is a many-to-many kind of interpretation problem. Some >>> problems are much simpler, but the complications is what makes general AI >>> so complex. >>> Jim Bromer >>> >>> On Sun, Dec 16, 2012 at 4:43 AM, Mike Tintner >>> <[email protected]>wrote: >>> >>> Logan, >>> You’re thinking of converting words into more words, here? >>> How do the words translate into a physical course of action? >>> How (i.e. in what forms of representation) would an infant AGI think >>> that hadn’t yet learned language, when it say wants to >>> “go across the room”... >>> crawl, roll, whatever across the carpet to a toy? >>> How do you get from “go” to its first and subsequent movements of >>> limbs? Bear in mind, that the same wish – the same formulation – could >>> apply to the infant in vastly diverse physical situations - initial >>> physical positions llike lying, sitting, lying on side, standing against >>> some object etc - and vastly different room configurations. >>> >>> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >>> <https://www.listbox.com/member/archive/rss/303/6952829-59a2eca5> | >>> Modify <https://www.listbox.com/member/?&;> Your Subscription >>> <http://www.listbox.com> >>> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >>> <https://www.listbox.com/member/archive/rss/303/19999924-5cfde295> | >>> Modify <https://www.listbox.com/member/?&;> Your Subscription >>> <http://www.listbox.com> >>> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >>> <https://www.listbox.com/member/archive/rss/303/6952829-59a2eca5> | >>> Modify <https://www.listbox.com/member/?&;> Your Subscription >>> <http://www.listbox.com> >>> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >>> <https://www.listbox.com/member/archive/rss/303/5037279-a88c7a6d> | >>> Modify <https://www.listbox.com/member/?&;> Your Subscription >>> <http://www.listbox.com> >>> >> >> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/6952829-59a2eca5> | >> Modify <https://www.listbox.com/member/?&;> Your Subscription >> <http://www.listbox.com> >> *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/5037279-a88c7a6d> | >> Modify <https://www.listbox.com/member/?&;> Your Subscription >> <http://www.listbox.com> >> > > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/6952829-59a2eca5> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <http://www.listbox.com> > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/5037279-a88c7a6d> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <http://www.listbox.com> > ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
