一、課程目標
本課程目標在於從大乘佛教哲學中的非單純實在論、非單純經驗論之認識論觀點，關照智慧、邏輯規則以及經驗成形之間的關係，同時比照在素樸實在論（時間空間為客觀實在框架）、素樸經驗論（暫時擱置經驗之前在條件），以及/或者在語意本體論框架下之當代人工智慧應用之觀點下，探討邏輯規則以及經驗成形之間的關係，以及「智慧」之可能性，或可能的詮釋方向。
二、課程內涵
（1）佛教認識論部分，我們從陳那的因明量論著手，藉由陳那在佛教認識論發展中承先啟後奠定佛教新因明的關鍵性貢獻，明瞭佛教認識論當中之主要問題意識。（2）理解當代認知科學研究之成果，理解知覺、意識以及自由意志相關的問題。（3）認識人工智慧領域幾個重要核心概念，例如符號型AI、類神經網路、機器學習、奇點、達特茅斯會議等；以及主要的哲學問題，包含人工智慧與自然智慧、圖靈測試、符號主義與連結主義、心物與心腦問題、強人工智慧vs.弱人工智慧等等。
1. Course objectives
The purpose of this course is to understand the non-single and non-single experience from Mahayana Buddhist philosophy, to follow the relationship between wisdom, logic rules and experience formation, and to compare the simple and practical discussion (time and space are the frame of the object view), Experience (temporarily place the conditions before the experience), and/or under the view of contemporary artificial intelligence applications under the framework of the intrinsic theory, explore the relationship between logic rules and experience formation, as well as the possibility of "wisdom", or possible directions of comments.
2. Course content
(1) In the Buddhist cognition, we start from Chen Na's theory of causality and judging, and through Chen Na's development of Buddhist cognition, we have established the key contribution of the new Buddhist cognition and judging, and understand the main problem and meaning of the Buddhist cognition and judging. (2) Understand the achievements of contemporary intellectual scientific research, and understand the problems related to knowledge, consciousness and free will. (3) Understand several important core concepts in the field of artificial intelligence, such as symbolic AI, neural network, machine learning, singularity, Datmouth Conference, etc.; as well as major philosophical problems, including artificial intelligence and natural wisdom, graphic testing, symbolicism and connection theory, mind and object and mind problems, strong artificial intelligence vs. weak artificial intelligence, etc.
1. 服部正明（著），吳汝鈞（譯）。〈陳那之認識論〉收錄于《佛學研究方法論》下冊之〈維也納學派方法〉。臺北：臺灣學生書局，2006。
2. 三宅陽一郎、森川幸人（著），鄭佩嵐（譯）。《從人到人工智慧，破解AI革命的68個核心概念》。臺北：城邦文化事業，2018。
3. 鄭谷苑（編）。《窺探心智》。《科學人博學誌》2017年11月。
1. Hattori Masayoshi (written), Wu Ruo (translation). "Chen Na's Awareness" is included in "Vienna School Methods" listed in "The Methods of Buddhist Research". Taipei: Taiwan Student Book Bureau, 2006.
2. Miyake Yaichiro, Morikawa Yukito (written), and Zheng Pei (translated). "From human to artificial intelligence, cracking 68 core concepts of the AI revolution." Taipei: City-State Cultural Affairs, 2018.
3. Zhengguyuan (editor). "Exploring the Mind". "Scientific Arts Journal" November 2017.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 每週研讀、報告、討論每週研讀、報告、討論 Weekly study, report, discussion |
30 | |
| 期中報告（口頭15分鐘簡報）期中報告（口頭15分鐘簡報） Midterm report (15-minute briefing on the mouth) |
30 | |
| 期末報告或企劃案期末報告或企劃案 Final report or plan |
40 |
