Instead of chopping off pieces of set duration it could just divide dtime into the smallest possible number of equal parts less than that duration.Īlso it looks to me like acceleration is actually applied twice, not sure though, just eyeballing it. null) return null Vector keyFramesVector new Vector() // create a. 0001 is around 1%, but the problem occurs around 50% of the time so something doesn't add up, or my calculations are off.Īnyway that loop looks weird and somehow eludes attention so it could probably use some review. Displays a simple driving type game scene, using texture mapped cubes : Scene 3D. Still the probablility that leftover dtime is less than. The problem is with the last piece which can be very small, actually there's a comment which shows the author was aware of precision problems involved. this example there is no game object with that name, so the Find() function returns null. An imputation is a payoff vector that is group rational and individually. This makes the Null Reference Exception easy to find and fix. What it does is chop up dtime into pieces of 0.01. By convention, we also speak of the empty set. Player is different though, the bad starts about here: clientenvironment.cpp:192 This effect is theoretically possible when dtime is less than 0.0001 (assuming acceleration is around 10) which occurs naturally at about 10 000 frames per second, so I'd say it's impossible enough and that's why entities are not affected. LinearAlgebra ZeroMatrix construct a zero Matrix ZeroVector construct a zero Vector Calling Sequence Parameters Description Examples Calling Sequence. In that trace speedY seems to be what comes in affected by acceleration, and in that particular spot it's perfectly fine for speed to be nonzero even when player stands still.
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But certainly I pay attention to any research I come across which seems like it might be germane. I think that the theory that 'procedural memory decay at the same rate as declarative memory' is a reasonable default theory, and I haven't noticed any real difference in average grade (accuracy of recall) for my programming cards and my more normal flashcards. This might simply require experimentation to settle? I dunno. I suspect the memory research that justifies spaced repetition might not apply to skill development as opposed to simple recognition and recall. Similar reasoning suggests that, it might be good to memorize the name and purpose of all the commonly tools that can be installed and run library in debian from the command line, and all the libraries that exist in one's preferred programming language. You can find and scan the books based on running into the problem in real life, but the existence of the books will (hopefully) be trigger by the simpler memories. That way you might hope to have instantaneous recall that something in the library will help when you run across a specific problem that books exist for. what subject is NZ? What are the three best selling non-fiction titles under NZ? That kind of thing. Something that occurred to me yesterday after jogging was that the best things to memorize are probably meta-reference material that's likely to be stable, like the library of congress non-fiction classification system. Would it be better to memorize 150 specific positions and where each one's best move is or have a new one every time and practice? I suspect the memory research that justifies spaced repetition might not apply to skill development as opposed to simple recognition and recall. When I was trying to find or imagine the best way to create something to study tesuji I ran into this. In that essay you touched on the possibility of creating practice problems that generate a new puzzle each time to build skills. Yes! Good essay! 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