Path: utzoo!utgpu!news-server.csri.toronto.edu!mailrus!cs.utexas.edu!sdd.hp.com!uakari.primate.wisc.edu!dali.cs.montana.edu!milton!wex@dali.pws.bull.com From: wex@dali.pws.bull.com (Buckaroo Banzai) Newsgroups: sci.virtual-worlds Subject: Re: "Space" Message-ID: Date: 17 Aug 90 22:44:28 GMT References: <9007250107.AA01311@hitl.vrnet.washington.edu> Sender: hlab@milton.u.washington.edu Organization: Bull Worldwide Information Systems Inc. Lines: 95 Approved: hitl@hardy.u.washington.edu In article schraudo%beowulf@ucsd.edu (Nici Schraudolph) writes: Sorry, but humans *don't* do well in general 3D. We spend most of our waking lives on a 2D surface, and have evolved to deal with that. Sure, there is altitude, but gravity and visual clues make the orientation problem along that dimension trivial: you always know which way the ground is. This is more or less the point Meredith Bricken made. I see your point, but I don't know any of these thing when I'm playing the various flight simulators (particularly in those modes that remove external cues like the horizon), and I don't do too badly. Besides, what's to stop us putting in all kinds of cognitive artifacts to help us out? In fact, I advocate doing just that. Landmarks are just one example. Wumpus is played in a 3D space with additional contraints: the only moves allowed are those between vertices of a dodekaeder. Thus Wumpus is an instantiation of the general 3D navigation problem, and it follows that your performance at general 3D navigation can't be better than at Wumpus. I don't see that this follows at all. I do much better in the flight simulators and 3D space-battle games than I do at Wumpus. you get the best mileage by imposing intuitive constraints that are gleaned from nature. I don't think so, but I'm willing to be proven wrong. What sort of experience do you base this idea on? From a cognitive perspective our natural environment might best be described as "2 + 1"D, and this concept is also beneficial when thinking about cyber- space implementations: adding a grid in the zero plane for one of the three coordinates (in case of a semantic space, preferably for the coordinate that represents the quality most "different" from the other two) will aid navigation through the VR, as will simulated gravity effects (eg. a tendency to slowly turn "right side up" in the absence of movement commands). Having a horizon is one of the first artifacts I'd put in. I'm not entirely sure about a grid, since it might interfere with seeing the objects. I'd like to get my hands on a good enough 3D rendering system that I could experiment with shadows. I'd put a single light source at a constant distance and simply allow shadows to appear (on the zero plane?). Again, though, this is implementation - not necessarily part of the theory. Sure. What I'm saying is the less artifacts you need to navigate a given data structure, the better your system, because you are obviously tapping more of the intuitive human navigation potential. Thus the zero-grid suggested above is preferable to having to consult a 3D-compass to find out which way you're headed. Again, I'm dubious about any claim that includes the word "obvious." What data do you base this idea on? I bet I can make a cybercompass that's better than your zero-grid, particularly when we're trying to find a place or object that's described by more than three interesting properties. Wait a minute - time-honored computer science data structures have been (and are being) invented precisely for the purpose of dealing with huge volumes of data! Sorry, but that's simply not the case. Flowcharts, trees, graphs, et al were invented *long* before there were million LOC programs. Indeed, at MCC we did field studies and found engineer after engineer who had been in the business for decades and who were growing increasingly frustrated that their time-tested methods simply couldn't help them with the increasingly complex problems they were facing. Implementing visual representations of these structures is a very valuable undertaking in cognitive engineering, and will give a performance advantage by exploiting intuitive human skills such as navigation. I don't find anything intuitive about a flowchart or a dataflow diagram or an entity-relation diagram. If you've got some other meaning of intuitive, or if you're talking about some other "representations" or "structures" please let me know. However, you seem to claim that your work provides ways of structuring data that are new in a more fundamental, abstract sense. This is a big claim that I have yet to be convinced of. We could play a little game: you name a feature in your system, I name the data structure it is a visual imple- mentation of. I'll be pleasantly surprised if I can't answer. OK, let's start with fisheye views. If that's too easy for you, try generalized degree-of-interest functions. In a sense it's a losing game for me in that if I ever hope to implement my theories I'm going to have to do it in terms of computationally-realizable structures, any of which are amenable to multiple conventional and unconventional representations. -- --Alan Wexelblat phone: (508)294-7485 Bull Worldwide Information Systems internet: wex@pws.bull.com "Politics is Comedy plus Pretense."