GOFAI
GOFAI(英語:Good Old-Fashioned Artificial Intelligence),有效的老式人工智慧。
在人工智慧領域,GOFAI泛指用最原始人工智慧的邏輯方法解決小領域的問題,例如棋類遊戲的演算法。
GOFAI最早出現於1986年,約翰·豪格蘭(John Haugeland)的《Artificial Intelligence: The Very Idea》。其主要內容詮釋了人工智慧的哲學意義,也提議人工智慧應歸類為合成智慧(synthetic intelligence),這個概念後來被某些非GOFAI研究者採納。
參見
編輯引文
編輯參考資料
編輯- Garcez, Artur; Besold, Tarek; De Raedt, Luc; Földiák, Peter; Hitzler, Pascal; Icard, Thomas; Kühnberger, Kai-Uwe; Lamb, Luís; Miikkulainen, Risto; Silver, Daniel. Neural-Symbolic Learning and Reasoning: Contributions and Challenges. AAI Spring Symposium - Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches. Stanford, CA: AAAI Press. 2015. doi:10.13140/2.1.1779.4243.
- Garcez, Artur d'Avila; Lamb, Luis C., Neurosymbolic AI: The 3rd Wave, 2020 [2022-07-14], arXiv:2012.05876 , (原始內容存檔於2022-12-22)
- 約翰·豪格蘭, Artificial Intelligence: The Very Idea, Cambridge, Mass: MIT Press, 1985, ISBN 0-262-08153-9
- Kautz, Henry. The Third AI Summer, Henry Kautz, AAAI 2020 Robert S. Engelmore Memorial Award Lecture. 2020 [2022-07-06]. (原始內容存檔於2022-10-05).
- Kautz, Henry. The Third AI Summer: AAAI Robert S. Engelmore Memorial Lecture. AI Magazine. 2022, 43 (1): 93–104 [2022-07-12]. ISSN 2371-9621. S2CID 248213051. doi:10.1609/aimag.v43i1.19122. (原始內容存檔於2022-10-07).
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- Marcus, Gary, The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence, arXiv, 2020 [2022-07-12], (原始內容存檔於2023-01-04)
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- Rossi, Francesca. AAAI2022: Thinking Fast and Slow in AI (AAAI 2022 Invited Talk). 2022-07-06 [2022-07-06]. (原始內容存檔於2022-10-08).
- 斯圖爾特·羅素; 彼德·諾米格. Artificial Intelligence: A Modern Approach 2nd. Upper Saddle River, N.J: Prentice Hall. 2003. ISBN 978-0-13-790395-5.
- 斯圖爾特·羅素; 彼德·諾米格. Artificial Intelligence: A Modern Approach 4th. Hoboken: Pearson. 2021. ISBN 9780134610993. LCCN 20190474.
- Selman, Bart. AAAI2022: Presidential Address: The State of AI. 2022-07-06 [2022-07-06]. (原始內容存檔於2022-09-28).
- Turing, A. M. I.—Computing Machinery and Intelligence. Mind. 1950, LIX (236): 433–460 [2022-09-14]. ISSN 0026-4423. doi:10.1093/mind/LIX.236.433.