Oct 10 2012: At the level of the basic unit, the fetch-execute cycle, computers (robots have brains which are computers) are open-loop devices. The other term which is similar to open-loop is 'feedforward'. They just do stuff, and dont worry about the consequences. Humans and animals use the closed-loop principle at the basic unit level. Some people (Clark Hull, Nikolaas Tinbergen) call this 'drive-based', but the term that is used most these days is 'feedback'. These basic units do stuff too, but they are concerned about the consequences - they sense the effects of their actions, which are 'fed back', usually in order to self-regulate these actions, ie maintain homeostasis. Sometimes they are used for 'positive feedback' - a cascade, eg a sneeze, an orgasm, cell mitosis/meiosis, neuron action impulse. These two systems are not dissimilar- in fact, a feedback cycle is just a feedforward link (eg an amplifier, a neural network -really any function block) with a feedback circuit added on.
Computers do have feedback circuits, but not at the hardware data level. We program them in at the software level - sometimes. As in other areas of mathematics, we have discrete (integral) types and analog (continuous) types. a discrete type of feedback is the IF-THEN loop. The IF condition is a switch- it uses fresh 'outside' (its own level) information to select which 'inside' procedural path to take. Therefore, using feedback produces computing units that are self-regulating, but also self-indeterminate. They rely on information in other units to achieve completion.
However, the basic criticism of the 'von Neumann bottleneck' remains- every bit of data must pass through a narrow feedforward funnel; very, very, very fast. To use feedback to regulate and correct these data, eg at the software level, involves introducing indeterminacy, and slows the whole machine down. Turns and roundabouts. To make an intelligent computer means mastering these two systems -feedforward vs feedback.
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Computers do have feedback circuits, but not at the hardware data level. We program them in at the software level - sometimes. As in other areas of mathematics, we have discrete (integral) types and analog (continuous) types. a discrete type of feedback is the IF-THEN loop. The IF condition is a switch- it uses fresh 'outside' (its own level) information to select which 'inside' procedural path to take. Therefore, using feedback produces computing units that are self-regulating, but also self-indeterminate. They rely on information in other units to achieve completion.
However, the basic criticism of the 'von Neumann bottleneck' remains- every bit of data must pass through a narrow feedforward funnel; very, very, very fast. To use feedback to regulate and correct these data, eg at the software level, involves introducing indeterminacy, and slows the whole machine down. Turns and roundabouts. To make an intelligent computer means mastering these two systems -feedforward vs feedback.