|Brockman I 147
Local minimum problem/local maximum/fitness landscape/Chris Anderson: The limits of gradient descent constitute the so-called local-minima problem (or local-maxima problem, if you’re doing a gradient ascent). >Fitness landscape. (>Local minimum).
Solution/Anderson: (…) you either need a mental model (i.e., a map) of the topology, so you know where to ascend to get out of the valley, or you need to switch between gradient descent and random walks so you can bounce your way out of the region. >Robots/Anderson, >Artificial intelligence/Anderson, >Universe/Anderson, >Fitness landscape.
Anderson, Chris “Gradient Descent” in: Brockman, John (ed.) 2019. Twenty-Five Ways of Looking at AI. New York: Penguin Press._____________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. 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.
The Long Tail: Why the Future of Business is Selling Less of More New York 2006
Possible Minds: Twenty-Five Ways of Looking at AI New York 2019