Zobrazeno 1 - 10
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pro vyhledávání: '"Eric B. Baum"'
Autor:
Eric B Baum
Publikováno v:
Neural Computation. 35:536-553
TruthSift is a cloud-based platform that logically combines members' contributions into a collective intelligence. Members add statements and directed connectors to diagrams. TruthSift monitors which statements have been logically established by demo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbb7ed3cead90ae39edb4b9320e9bb53
https://doi.org/10.1162/neco_a_01562
https://doi.org/10.1162/neco_a_01562
Autor:
Eric B. Baum
In What Is Thought? Eric Baum proposes a computational explanation of thought. Just as Erwin Schrodinger in his classic 1944 work What Is Life? argued ten years before the discovery of DNA that life must be explainable at a fundamental level by physi
Autor:
Eric B. Baum, Yuh-Dauh Lyuu
Publikováno v:
Neural computation. 3(3)
Several recent papers (Gardner and Derrida 1989; Györgyi 1990; Sompolinsky et al. 1990) have found, using methods of statistical physics, that a transition to perfect generalization occurs in training a simple perceptron whose weights can only take
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d7369f661c5f4c34e2ca38b40c04169
https://pubmed.ncbi.nlm.nih.gov/31167314
https://pubmed.ncbi.nlm.nih.gov/31167314
Autor:
Eric B. Baum
Publikováno v:
The Economy as an Evolving Complex System ISBN: 9780429492846
I review the Hopfield model, feedforward models for associative memory, and the back-propagation learning algorithm for supervised learning.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2ddb5b883510725702e0ef632db6c62
https://doi.org/10.1201/9780429492846-3
https://doi.org/10.1201/9780429492846-3
Autor:
Laura F. Landweber, Eric B. Baum
The fledgling field of DNA computers began in 1994 when Leonard Adleman surprised the scientific community by using DNA molecules, protein enzymes, and chemicals to solve an instance of a hard computational problem. This volume presents results from
Autor:
Richard J. Lipton, Eric B. Baum
This volume presents the proceedings of a conference held at Princeton University in April 1995 as part of the DIMACS Special Year on Mathematical Support for Molecular Biology. The subject of the conference was the new area of DNA based computing. D
Autor:
Gary W. Flake, Eric B. Baum
Publikováno v:
Theoretical Computer Science. 270:895-911
Rush Hour is a children's game that consists of a grid board, several cars that are restricted to move either vertically or horizontally (but not both), a special target car, and a single exit on the perimeter of the grid. The goal of the game is to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7603b014bbd4aed8009cd5bd1f4d4f1e
https://doi.org/10.1016/s0304-3975(01)00173-6
https://doi.org/10.1016/s0304-3975(01)00173-6
Autor:
Eric B. Baum
Publikováno v:
Machine Learning. 35:155-185
A market-based algorithm is presented which autonomously apportions complex tasks to multiple cooperating agents giving each agent the motivation of improving performance of the whole system. A specific model, called “The Hayek Machine” is propos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8109575f9e38548dd1c6d5a8b9fef588
https://doi.org/10.1023/a:1007593124513
https://doi.org/10.1023/a:1007593124513
Autor:
Eric B. Baum, Warren D. Smith
Publikováno v:
Neural Computation. 11:215-227
In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9ed18285fd98681d21436bf558160af
https://doi.org/10.1162/089976699300016881
https://doi.org/10.1162/089976699300016881
Autor:
Warren D. Smith, Eric B. Baum
Publikováno v:
Artificial Intelligence. 97(1-2):195-242
The point of game tree search is to insulate oneself from errors in the evaluation function. The standard approach is to grow a full width tree as deep as time allows, and then value the tree as if the leaf evaluations were exact. The alpha-beta algo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e58194293075f59e0d2d5536e340ead