| http://dbpedia.org/ontology/abstract
|
GOFAI（英語：Good Old-Fashioned Artificial Int … GOFAI（英語：Good Old-Fashioned Artificial Intelligence），有效的老式人工智能。 在人工智能领域，GOFAI泛指用最原始的人工智能的逻辑方法解决小领域的问题，例如棋类游戏的算法。 GOFAI最早出现于1986年，（John Haugeland）的《Artificial Intelligence: The Very Idea》。其主要内容诠释了人工智能的哲学意义，也提议人工智能应归类为合成智能（synthetic intelligence），这个概念后来被某些非GOFAI研究者采纳。thetic intelligence），这个概念后来被某些非GOFAI研究者采纳。
, GOFAI is an acronym for "Good Old-Fashione … GOFAI is an acronym for "Good Old-Fashioned Artificial Intelligence" invented by the philosopher John Haugeland in his 1985 book, Artificial Intelligence: The Very Idea. Technically, GOFAI refers only to a restricted kind of symbolic AI, namely rule-based or logical agents. This approach was popular in the 1980s, especially as an approach to implementing expert systems, but symbolic AI has since been extended in many ways to better handle uncertain reasoning and more open-ended systems. Some of these extensions include probabilistic reasoning, non-monotonic reasoning, multi-agent systems, and neuro-symbolic systems. Significant contributions of symbolic AI, not encompassed by the GOFAI view, include search algorithms; automated planning and scheduling; constraint-based reasoning; the semantic web; ontologies; knowledge graphs; non-monotonic logic; circumscription; automated theorem proving; and symbolic mathematics. For a more complete list, see the main article on symbolic AI.list, see the main article on symbolic AI.
|
| http://dbpedia.org/ontology/wikiPageExternalLink
|
https://www.youtube.com/watch%3Fv=_cQITY0SPiw +
, https://doi.org/10.1093/mind/LIX.236.433 +
, https://ojs.aaai.org/index.php/aimagazine/article/view/19122 +
, https://aaai-2022.virtualchair.net/plenary_2.html +
, http://arxiv.org/abs/2002.06177 +
, http://arxiv.org/abs/2012.05876 +
, https://aaai-2022.virtualchair.net/plenary_13.html +
|
| http://dbpedia.org/ontology/wikiPageID
|
44636570
|
| http://dbpedia.org/ontology/wikiPageInterLanguageLink
|
http://zh-yue.dbpedia.org/resource/GOFAI +
|
| http://dbpedia.org/ontology/wikiPageLength
|
16988
|
| http://dbpedia.org/ontology/wikiPageRevisionID
|
1121448845
|
| http://dbpedia.org/ontology/wikiPageWikiLink
|
http://dbpedia.org/resource/Resource_Description_Framework +
, http://dbpedia.org/resource/Stuart_J._Russell +
, http://dbpedia.org/resource/Qualification_problem +
, http://dbpedia.org/resource/Knowledge_graph +
, http://dbpedia.org/resource/Association_rule_learning +
, http://dbpedia.org/resource/Expert_system +
, http://dbpedia.org/resource/Case-based_reasoning +
, http://dbpedia.org/resource/Advice_taker +
, http://dbpedia.org/resource/Bayesian_inference +
, http://dbpedia.org/resource/Search_algorithms +
, http://dbpedia.org/resource/Judea_Pearl +
, http://dbpedia.org/resource/Inductive_logic_programming +
, http://dbpedia.org/resource/Peter_Norvig +
, http://dbpedia.org/resource/Computing_Machinery_and_Intelligence +
, http://dbpedia.org/resource/Non-monotonic_logic +
, http://dbpedia.org/resource/Lisp_machine +
, http://dbpedia.org/resource/Deep_learning +
, http://dbpedia.org/resource/Artificial_Intelligence:_A_Modern_Approach +
, http://dbpedia.org/resource/Hubert_Dreyfus +
, http://dbpedia.org/resource/Category:Terms_in_science_and_technology +
, http://dbpedia.org/resource/Stuart_Dreyfus +
, http://dbpedia.org/resource/Ontology_%28information_science%29 +
, http://dbpedia.org/resource/Chunking_%28psychology%29 +
, http://dbpedia.org/resource/Semantic_Web +
, http://dbpedia.org/resource/Knowledge_engineering +
, http://dbpedia.org/resource/Tom_M._Mitchell +
, http://dbpedia.org/resource/Embodied_cognition +
, http://dbpedia.org/resource/Multi-agent_system +
, http://dbpedia.org/resource/Production_system_%28computer_science%29 +
, http://dbpedia.org/resource/Argumentation_framework +
, http://dbpedia.org/resource/Symbolic_AI +
, http://dbpedia.org/resource/Circumscription_%28logic%29 +
, http://dbpedia.org/resource/Web_Ontology_Language +
, http://dbpedia.org/resource/Symbolic_mathematics +
, http://dbpedia.org/resource/Probabilistic_logic +
, http://dbpedia.org/resource/Semantic_network +
, http://dbpedia.org/resource/Statistical_relational_learning +
, http://dbpedia.org/resource/Machine_learning +
, http://dbpedia.org/resource/Probably_approximately_correct_learning +
, http://dbpedia.org/resource/Inference_engine +
, http://dbpedia.org/resource/John_Haugeland +
, http://dbpedia.org/resource/Leslie_Valiant +
, http://dbpedia.org/resource/Modal_logic +
, http://dbpedia.org/resource/Andy_Clark +
, http://dbpedia.org/resource/Constraint_satisfaction_problem +
, http://dbpedia.org/resource/Version_space_learning +
, http://dbpedia.org/resource/Kenneth_M._Sayre +
, http://dbpedia.org/resource/Decision_tree_learning +
, http://dbpedia.org/resource/Knowledge_representation_and_reasoning +
, http://dbpedia.org/resource/Category:Artificial_intelligence +
, http://dbpedia.org/resource/Automated_planning_and_scheduling +
, http://dbpedia.org/resource/Symbolic_artificial_intelligence +
, http://dbpedia.org/resource/Neuro-symbolic_AI +
, http://dbpedia.org/resource/Commonsense_reasoning +
, http://dbpedia.org/resource/Automated_theorem_proving +
, http://dbpedia.org/resource/YAGO_%28database%29 +
, http://dbpedia.org/resource/Situated +
, http://dbpedia.org/resource/Alan_Turing +
, http://dbpedia.org/resource/Geoffrey_Hinton +
, http://dbpedia.org/resource/Inductive_programming +
|
| http://dbpedia.org/property/wikiPageUsesTemplate
|
http://dbpedia.org/resource/Template:Cite_AV_media +
, http://dbpedia.org/resource/Template:Cite_journal +
, http://dbpedia.org/resource/Template:Cite_web +
, http://dbpedia.org/resource/Template:Reflist +
, http://dbpedia.org/resource/Template:Citation +
, http://dbpedia.org/resource/Template:Cite_conference +
, http://dbpedia.org/resource/Template:About +
, http://dbpedia.org/resource/Template:Sfnp +
, http://dbpedia.org/resource/Template:Sfn +
, http://dbpedia.org/resource/Template:Cite_book +
|
| http://purl.org/dc/terms/subject
|
http://dbpedia.org/resource/Category:Artificial_intelligence +
, http://dbpedia.org/resource/Category:Terms_in_science_and_technology +
|
| http://www.w3.org/ns/prov#wasDerivedFrom
|
http://en.wikipedia.org/wiki/GOFAI?oldid=1121448845&ns=0 +
|
| http://xmlns.com/foaf/0.1/isPrimaryTopicOf
|
http://en.wikipedia.org/wiki/GOFAI +
|
| owl:sameAs |
https://global.dbpedia.org/id/6Zvwg +
, http://zh.dbpedia.org/resource/GOFAI +
, http://www.wikidata.org/entity/Q85872860 +
, http://dbpedia.org/resource/GOFAI +
|
| rdfs:comment |
GOFAI is an acronym for "Good Old-Fashione … GOFAI is an acronym for "Good Old-Fashioned Artificial Intelligence" invented by the philosopher John Haugeland in his 1985 book, Artificial Intelligence: The Very Idea. Technically, GOFAI refers only to a restricted kind of symbolic AI, namely rule-based or logical agents. This approach was popular in the 1980s, especially as an approach to implementing expert systems, but symbolic AI has since been extended in many ways to better handle uncertain reasoning and more open-ended systems. Some of these extensions include probabilistic reasoning, non-monotonic reasoning, multi-agent systems, and neuro-symbolic systems. Significant contributions of symbolic AI, not encompassed by the GOFAI view, include search algorithms; automated planning and scheduling; constraint-based reasoning; the semaning; constraint-based reasoning; the seman
, GOFAI（英語：Good Old-Fashioned Artificial Int … GOFAI（英語：Good Old-Fashioned Artificial Intelligence），有效的老式人工智能。 在人工智能领域，GOFAI泛指用最原始的人工智能的逻辑方法解决小领域的问题，例如棋类游戏的算法。 GOFAI最早出现于1986年，（John Haugeland）的《Artificial Intelligence: The Very Idea》。其主要内容诠释了人工智能的哲学意义，也提议人工智能应归类为合成智能（synthetic intelligence），这个概念后来被某些非GOFAI研究者采纳。thetic intelligence），这个概念后来被某些非GOFAI研究者采纳。
|
| rdfs:label |
GOFAI
|
