The Evolution of Vagueness
The Evolution of Vagueness
复制标题
模糊性的演变
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Cailin O’Connor
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文献类型：
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作者：
Cailin O’Connor
模糊谓词，即那些展示边界情况的谓词，给哲学家和逻辑学家带来了一个长期存在的问题。尽管模糊谓词在自然语言中普遍存在，但在逻辑语境中使用时，模糊谓词会导致矛盾。本文将讨论与这一问题密切相关的一个问题。鉴于模糊谓词固有的不精确性，为什么首先会出现模糊谓词呢？我讨论了信号博弈的一种变体，其中状态空间被视为连续的，即被赋予一个度量，该度量捕捉状态上的相似关系。这种增加的结构体现在回报上，奖励发送者和接收者之间的近似协调以及完美的协调。我使用Herrnstein强化学习的变体来演变这些游戏，该变体更好地反映了现实世界中的参与者在世界状态相似的情况下使用的泛化学习策略。在这些模拟中，信号可以非常迅速地发展，并且信号在很大程度上是模糊的，就像普通语言的谓词模糊一样--它们各自只适用于某些项，但在某个过渡期，这两个信号都适用不同的程度。此外，我还证明了在某些参数值下，特别是当状态空间较大且时间有限时，这种学习推广产生的策略比标准Herrnstein强化学习具有更高的回报。然后，这些模型可能有助于解释为什么自然语言中会出现模糊现象：允许参与者在连续的状态空间中快速有效地发展信号约定的学习策略使其不可避免。
Vague predicates, those that exhibit borderline cases, pose a persistent problem for philosophers and logicians. Although they are ubiquitous in natural language, when used in a logical context, vague predicates lead to contradiction. This paper will address a question that is intimately related to this problem. Given their inherent imprecision, why do vague predicates arise in the first place? I discuss a variation of the signaling game where the state space is treated as contiguous, i.e., endowed with a metric that captures a similarity relation over states. This added structure is manifested in payoffs that reward approximate coordination between sender and receiver as well as perfect coordination. I evolve these games using a variation of Herrnstein reinforcement learning that better reflects the generalizing learning strategies real-world actors use in situations where states of the world are similar. In these simulations, signaling can develop very quickly, and the signals are vague in much the way ordinary language predicates are vague—they each exclusively apply to certain items, but for some transition period both signals apply to varying degrees. Moreover, I show that under certain parameter values, in particular when state spaces are large and time is limited, learning generalization of this sort yields strategies with higher payoffs than standard Herrnstein reinforcement learning. These models may then help explain why the phenomenon of vagueness arises in natural language: the learning strategies that allow actors to quickly and effectively develop signaling conventions in contiguous state spaces make it unavoidable.