Intelligent Systems And Their Societies Walter Fritz



Feedback, reinforcement, is a very important mechanism that increases the value of some response rules and decreases the value of others. Feedback is provided to the brain from two very different sources:

  1. by the environment, through effects on the body,
  2. by a "teacher's" intentional communication.
This second method does not only occur in the case of school. It also happens at other times such as at play by friends, at work by the boss, and from other employees or business associates acting as a "teacher". Through this feedback, response rules are increased or decreased in value, as needed.


Traditionally, there are two, very unequal types of reinforcement: negative and positive. Negative reinforcement makes less probable the use of a non-optimal response rule. However, it does not show which response rule to use in the future instead. If, on the other hand, a good response receives positive reinforcement, the IS will both increase the values of the response rule it used, and, in the next sleep period, create a more general response rule of high value that it is then likely to use in the future.

Thus, we can see that this is a classic case where the "carrots" of approval that characterize positive feedback have a different and much more useful effect in the learning cycles of an IS than does only the "stick" of negative reinforcement.

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Last Edited 6 Mar. 06 / Walter Fritz
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