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Marvin Minsky on Motivation - Dictionary of Arguments

I 168
Motivation/Minsky: Imagine that a thirsty child has learned to reach for a nearby cup. What keeps that child, afterward, from reaching for a cup in every other circumstance — say, when it is lonely or when it is cold? How do we keep separate what we learn for satisfying different goals?
Artificial Intelligence/actions/goals/Minsky: One way is to maintain a separate memory bank for every distinct goal. To make this work, we must restrict each specialist to learn only when its own goal is active. We can accomplish that by building them into a cross-exclusion system so that, for example, Hunger's memories can be formed only when Hunger is active. Such a system will never get confused about which memories to use.
Problem: (…) it would be too extravagant to have to keep completely different memories for every goal (…).
Wouldn't it be better if all those specialists could share a common, general-purpose memory?
Problem: Whenever any specialist tried to rearrange some memories to its own advantage, it might damage structures upon which the others have come to depend. There would be too many unpredictable interactions
Solution: Society of Minds: If they were like people, they could communicate, negotiate, and organize. But because each separate specialist is much too small and specialized to understand how the others work, the best each can do is learn to exploit what the others can do, without understanding how they do it. >Society of Minds/Minsky.


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Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments
The note [Author1]Vs[Author2] or [Author]Vs[term] is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition.

Minsky I
Marvin Minsky
The Society of Mind New York 1985

Minsky II
Marvin Minsky
Semantic Information Processing Cambridge, MA 2003


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Ed. Martin Schulz, access date 2021-06-17
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