北京大学语言、逻辑、认知与计算(LLCC)跨学科论坛两场报告
时间:2018年12月14日(周四)下午 2点 - 6点
报告一:Informativity vs applicability: Decision-theoretic approaches to the semantics and pragmatics of gradable adjectives (and beyond)
报告人:青慈阳(斯坦福大学)
时间:12月14日周四下午2点
地点:北京大学哲学系(人文学苑2号楼)地下B114
摘要: This talk starts with an introduction to the formal semantics of gradable adjectives such as tall and full, focusing on the interpretation of the positive (unmarked) form of gradable adjectives (e.g., tall in John is tall). As Kennedy (2007) observes, there are two subclasses of gradable adjectives: (i) relative adjectives such as tall and big, which are vague, and (ii) absolute adjectives such as full and straight, which are not vague (or at the very least, much less vague). I will review recent decision-theoretic approaches to the semantics and pragmatics of gradable adjectives that provide a unified explanation of the differences between relative and absolute adjectives in terms of a trade-off between informativity and applicability (Lassiter & Goodman's 2013, 2015; Qing & Franke 2014a). Moreover, these approaches make quantitative predictions that can be experimentally tested (Qing & Franke 2014b). Finally, I will review recent works that apply informativity-applicability trade-off to analyze phenomena in other domains.
主讲人简介:青慈阳,本科毕业于北京大学数学学院,
报告二:
题目:从隐性知识挖掘到整体思维模拟——以体征数据分析为例
主讲人:董军 (中科院苏州纳米技术与纳米仿生研究所)
时间:12月14日周四下午4点
地点:北京大学哲学系(人文学苑2号楼)地下B114
摘要:人工智能超过一个甲子的沉浮历程告诉我们,
主讲人简介:董军,男,1997年获浙江大学工学博士学位,20