Computability-logic web: an alternative to deep learning
{\em Computability logic} (CoL) is a powerful, mathematically rigorous computational model. In this paper, we show that CoL-web, a web extension to CoL, naturally supports web programming where database updates are involved. To be specific, we discuss an implementation of the AI ATM based on CoL (CL...
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creator | Kwon, Keehang |
description | {\em Computability logic} (CoL) is a powerful, mathematically rigorous
computational model. In this paper, we show that CoL-web, a web extension to
CoL, naturally supports web programming where database updates are involved. To
be specific, we discuss an implementation of the AI ATM based on CoL (CL9 to be
exact). More importantly, we argue that CoL-web supports a general AI and,
therefore, is a good alternative to neural nets and deep learning. We also
discuss how to integrate neural nets into CoL-web. |
doi_str_mv | 10.48550/arxiv.2101.09222 |
format | Article |
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computational model. In this paper, we show that CoL-web, a web extension to
CoL, naturally supports web programming where database updates are involved. To
be specific, we discuss an implementation of the AI ATM based on CoL (CL9 to be
exact). More importantly, we argue that CoL-web supports a general AI and,
therefore, is a good alternative to neural nets and deep learning. We also
discuss how to integrate neural nets into CoL-web.</description><identifier>DOI: 10.48550/arxiv.2101.09222</identifier><language>eng</language><subject>Computer Science - Artificial Intelligence ; Computer Science - Distributed, Parallel, and Cluster Computing</subject><creationdate>2020-11</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2101.09222$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2101.09222$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Kwon, Keehang</creatorcontrib><title>Computability-logic web: an alternative to deep learning</title><description>{\em Computability logic} (CoL) is a powerful, mathematically rigorous
computational model. In this paper, we show that CoL-web, a web extension to
CoL, naturally supports web programming where database updates are involved. To
be specific, we discuss an implementation of the AI ATM based on CoL (CL9 to be
exact). More importantly, we argue that CoL-web supports a general AI and,
therefore, is a good alternative to neural nets and deep learning. We also
discuss how to integrate neural nets into CoL-web.</description><subject>Computer Science - Artificial Intelligence</subject><subject>Computer Science - Distributed, Parallel, and Cluster Computing</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj7tuwjAUQL0wVNAP6IR_IKmfsc2Gor4kJBb26BpfI0smiYxLy99XpZ3OdnQOIU-ctcpqzZ6hfKdrKzjjLXNCiAdi--k8f1bwKad6a_J0Skf6hX5DYaSQK5YRaroirRMNiDPNCGVM42lFFhHyBR__uSSH15dD_97s9m8f_XbXQGdEI4WNXvkAQUbDhHC8M1oj8ygD94ZFZZA7UNbbaH0XGAMUMSA45exRg1yS9Z_2nj7MJZ2h3IbfheG-IH8AthNBTw</recordid><startdate>20201120</startdate><enddate>20201120</enddate><creator>Kwon, Keehang</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20201120</creationdate><title>Computability-logic web: an alternative to deep learning</title><author>Kwon, Keehang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a672-328fb4bdad3f7022916755e0be3d1b70f47e19a48b8f8b6d00ae2fdea9498c5a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Computer Science - Artificial Intelligence</topic><topic>Computer Science - Distributed, Parallel, and Cluster Computing</topic><toplevel>online_resources</toplevel><creatorcontrib>Kwon, Keehang</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kwon, Keehang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computability-logic web: an alternative to deep learning</atitle><date>2020-11-20</date><risdate>2020</risdate><abstract>{\em Computability logic} (CoL) is a powerful, mathematically rigorous
computational model. In this paper, we show that CoL-web, a web extension to
CoL, naturally supports web programming where database updates are involved. To
be specific, we discuss an implementation of the AI ATM based on CoL (CL9 to be
exact). More importantly, we argue that CoL-web supports a general AI and,
therefore, is a good alternative to neural nets and deep learning. We also
discuss how to integrate neural nets into CoL-web.</abstract><doi>10.48550/arxiv.2101.09222</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Artificial Intelligence Computer Science - Distributed, Parallel, and Cluster Computing |
title | Computability-logic web: an alternative to deep learning |
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