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Reflexes - artificial intelligence:
If an agent decides upon and executes an action in response to a sensor input without consultation of its world, then this can be considered a reflex response. Humans flinch if they touch something very hot, regardless of the particular social situation they are in, and this is clearly a reflex action. Similarly, chess agents are programmed with important tables for openings and endings, so that they do not have to do any processing to choose the exact shift they simply look it up. In timed chess matches, this kind of reflex action might keep vital seconds to be used in more hard situations later.
Unfortunately, relying on lookup tables is not a sensible way to program intelligent an agents: a chess agent would need 35100 entries in its lookup table (considerably more entries than there are atoms in the universe). And if we remember that the world of a chess agent consists of only 32 pieces on 64 squares, it's obvious that we need more intelligent means of choosing a rational action.
For RHINO, it's tough to discover any reflex actions. This is probably because performing an action without consulting the world representation is potentially hazardous for RHINO, because people get everywhere, and museum exhibits are expensive to replace if broken or damage!!
Avoiding Overfitting : However remember there that in the previous lecture, there is over fitting that common problem in machine learning. Furthermore details to decision tree
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Q. Binary floating-point number range? Smallest Negative number Maximum mantissa and maximum exponent = - (1 -2 -24 ) × 2 127 Largest negative number
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