Enactivism and predictive processing: a non-representational view

This paper starts by considering an argument for thinking that predictive processing (PP) is representational. This argument suggests that the Kullback–Leibler (KL)-divergence provides an accessible measure of misrepresentation, and therefore, a measure of representational content in hierarchical Bayesian inference. The paper then argues that while the KL-divergence is a measure of information, it does not establish a sufficient measure of representational content. We argue that this follows from the fact that the KL-divergence is a measure of relative entropy, which can be shown to be the same as covariance (through a set of additional steps). It is well known that facts about covariance do not entail facts about representational content. So there is no reason to think that the KL-divergence is a measure of (mis-)representational content. This paper thus provides an enactive, non-representational account of Bayesian belief optimisation in hierarchical PP.     

The embodiment of beauty: Evidence from viewing Chinese concrete words and pictographs

How is beauty embodied? According to the viewpoint of embodied cognition, the aesthetic processing of words or pictographs has roots in their referential archetypes. Four experiments tested whether the beauty of referential archetypes was routinely activated during the explicit and implicit aesthetic evaluations of the font structures of concrete Chinese words and pictographs in congruent or incongruent font colour. Results showed font structures of simplified Chinese words and pictographs were judged to be more beautiful when they referred to beautiful archetypes; and this pattern was reversed when they referred to ugly archetypes. Moreover, judgement was facilitated when font colour was congruent for Chinese words and pictographs referred to beautiful archetypes. For those referred to ugly archetypes, judgement was inhibited in congruent font colour but facilitated in incongruent font colour, suggesting aesthetic perceptions of the font structures of Chinese words and pictographs were derived from their referential natural objects. The spontaneous generation hypothesis of beauty is proposed to account for these findings.     

Categorical Ontology of Levels and Emergent Complexity: An Introduction

An overview of the following three related papers in this issue presents the Emergence of Highly Complex Systems such as living organisms, man, society and the human mind from the viewpoint of the current Ontological Theory of Levels. The ontology of spacetime structures in the Universe is discussed beginning with the quantum level; then, the striking emergence of the higher levels of reality is examined from a categorical—relational and logical viewpoint. The ontological problems and methodology aspects discussed in the first two papers are followed by a rigorous paper based on Category Theory, Algebraic Topology and Logic that provides a conceptual and mathematical basis for a Categorical Ontology Theory of Levels. The essential links and relationships between the following three papers of this issue are pointed out, and further possible developments are being considered.     

The Tense Logic for Master Argument in Prior’s Reconstruction

In this paper we examine Prior’s reconstruction of Master Argument [4] in some modal-tense logic. This logic consists of a purely tense part and Diodorean definitions of modal alethic operators. Next we study this tense logic in the pure tense language. It is the logic K _t 4 plus a new axiom (P): ‘p Λ G p ⊃ P G p’. This formula was used by Prior in his original analysis of Master Argument. (P) is usually added as an extra axiom to an axiomatization of the logic of linear time. In that case the set of moments is a total order and must be left-discrete without the least moment. However, the logic of Master Argument does not require linear time. We show what properties of the set of moments are exactly forced by (P) in the reconstruction of Prior. We make also some philosophical remarks on the analyzed reconstruction. Presented by Jacek Malinowski     

Uncovering deterministic causal structures: a Boolean approach

While standard procedures of causal reasoning as procedures analyzing causal Bayesian networks are custom-built for (non-deterministic) probabilistic structures, this paper introduces a Boolean procedure that uncovers deterministic causal structures. Contrary to existing Boolean methodologies, the procedure advanced here successfully analyzes structures of arbitrary complexity. It roughly involves three parts: first, deterministic dependencies are identified in the data; second, these dependencies are suitably minimalized in order to eliminate redundancies; and third, one or—in case of ambiguities—more than one causal structure is assigned to the minimalized deterministic dependencies.     

论管仲学派生态伦理思想的层次结构

管仲学派把天、地、人看作是一个以"道"为根据和调节机制的有机系统,认为天地人遵循着共同的基本生存法则,由此阐述了以"人与天调"、"天人相因"为基础的生态存在论。《管子》一书以"道为物要"的价值观为总依据,把自然现象道德化,根据人类道德与自然万物的内在依存关系,提出"德润万物"的生态伦理命题;揭示了自然现象的属性与人的能力品质的一致性,主张入世行为要遵循以"人与天调"、"德润万物"、"时之处事"为中心的伦理原则,并提出了取用有度的生态伦理规范,即合理利用,开发有度;依时禁放,顺天应人;宽猛并济,令行禁止;多管齐下,综合治理。管仲学派的生态伦理思想与其政治思想是紧密结合的,直接服务于治国安邦、发展经济和满足民众需求,它开创了中国生态伦理思想史的先河。     

Checking for Systematic Value Preferences Using the Method of Triads

Value preferences have long been central to research in political science and psychology. Despite their well‐established theoretical importance, however, their measurement is still an open question. Early research on values relied heavily on ranking instruments for data collection, but more recent work calls this measurement technique into question. Specifically, it is argued that traditional ranking instruments are (1) too long, (2) too complex, and (3) may force respondents to make ad hoc differentiations between values of similar importance, behind which there is no systematic preference. As a result, the reliability of the measure is called into question, and measurement error remains a concern. In this article, we discuss the method of triads—a technique used to gather rankings data that affords the researcher the opportunity to assess the extent to which random error affects preference rankings. Using the method of triads to collect preference data on five values central to American political culture, we find that Americans' value preferences are clearly structured and driven by systematic preferences, even when psychological theory suggests they may not. We also compare the predictive validity of the data collected with the method of triads against that of the data collected with traditional importance ratings. We show that models of ideology, party identification, presidential approval, and vote‐choice fit to “triads” data explain more variance than models fit to ratings data.     

谱聚类算法在不同属性层级结构诊断评估中的应用

聚类分析已成功用于认知诊断评估(CDA)中,使用广泛的聚类分析方法为K-means算法,有研究已证明K-means在CDA中具有较好的聚类效果。而谱聚类算法通常比K-means分类效果更佳,本研究将谱聚类算法引进CDA,探讨了属性层级结构、属性个数、样本量和失误率对该方法的影响。研究发现：（1）谱聚类算法要比K-means提供更好的聚类结果,尤其在实验条件较苛刻时,谱聚类算法更加稳健;（2）线型结构聚类效果最好,收敛型和发散型相近,独立型结构表现较差;（3）属性个数和失误率增加后,聚类效果会下降;（4）样本量增加后,聚类效果有所提升,但K-means方法有时会有反向结果出现。