Decomposition Proof Systems for Gödel-Dummett Logics

The main goal of the paper is to suggest some analytic proof systems for LC and its finite-valued counterparts which are suitable for proof-search. This goal is achieved through following the general Rasiowa-Sikorski methodology for constructing analytic proof systems for semantically-defined logics. All the systems presented here are terminating, contraction-free, and based on invertible rules, which have a local character and at most two premises.     

Typicality, graded membership, and vagueness

This paper addresses theoretical problems arising from the vagueness of language terms, and intuitions of the vagueness of the concepts to which they refer. It is argued that the central intuitions of prototype theory are sufficient to account for both typicality phenomena and psychological intuitions about degrees of membership in vaguely defined classes. The first section explains the importance of the relation between degrees of membership and typicality (or goodness of example) in conceptual categorization. The second and third section address arguments advanced by Osherson and Smith (1997), and Kamp and Partee (1995), that the two notions of degree of membership and typicality must relate to fundamentally different aspects of conceptual representations. A version of prototype theory-the Threshold Model-is proposed to counter these arguments and three possible solutions to the problems of logical selfcontradiction and tautology for vague categorizations are outlined. In the final section graded membership is related to the social construction of conceptual boundaries maintained through language use.     

A consistency-based framework for merging knowledge bases

We present a framework for expressing various merging operators for belief sets. This framework generalises our earlier work on consistency-based belief revision and contraction. Two primary merging operators are identified: in the first approach, belief sources are consistently combined so that the result of merging knowledge bases K₁,…,K_n is a maximal consistent (if possible) set of formulas comprising the joint knowledge of the knowledge bases. This approach then accords with one's intuitions as to what a “merge” operator should do. The second approach is more akin to a generalised belief revision operator. Knowledge bases K₁,…,K_n are “projected” onto another (in the simplest case the knowledge base where only tautologies are known). Properties of these operators are investigated, primarily by comparing their properties with postulates that have been identified previously in the literature. Notably, the approach is independent of syntax, in that merging knowledge bases K₁,…,K_n is independent of how each K_i is expressed. As well, we investigate the role of entailment-based and consistency-based integrity constraints, the interrelationships between these approaches and belief revision, and the expression of further merging operators.     

知觉负载、注意定势与选择性注意

本研究采用Eriksen Flanker（侧抑制）范式,将当前任务区分为高、低知觉负载两种条件．并系统操纵边缘视野干扰项与中央靶子的不同加工层次关系,从而考察注意选择的知觉负载理论。实验一发现,高知觉负载情况下没有任何flanker冲突效应,而低知觉负载情况下既有知觉层次和反应层次的冲突效应,也有一致条件下的促进效应。实验二增加了一致条件试次的比例,从而操纵自上而下的注意定势,发现高、低知觉负载情况下都存在知觉冲突效应和一致条件下的促进效应。这些发现表明,对任务无关信息的加工既受到任务相关信息的知觉负载和剩余加工资源的分配的影响,也受到自上而下注意定势的影响;自下而上和自上而下过程相互作用,共同决定加工资源的分配和注意选择的认知阶段。     

注意瞬脱的瓶颈理论

综述了注意瞬脱的瓶颈理论的相关研究。主要包括：（1）高级中枢加工瓶颈形成的两阶段模型、中枢干扰理论、TLC假设和注意的延迟投入假设;（2）目标选择的控制瓶颈形成的输入过滤器与目标模板假说;（3）同时类型系列标记模型。最后从瓶颈理论在整个注意瞬脱理论中的片面性和注意瞬脱的瓶颈理论本身的不完善性两方面剖析了瓶颈理论的局限性     

A fuzzy-based driver assistance system using human cognitive parameters and driving style information

Reducing the number of traffic accidents due to human errors is an urgent need in several countries around the world. In this scenario, the use of human-robot interaction (HRI) strategies has recently shown to be a feasible solution to compensate human limitations while driving. In this work we propose a HRI system which uses the driver’s cognitive factors and driving style information to improve safety. To achieve this, deep neural networks based approaches are used to detect human cognitive parameters such as sleepiness, driver’s age and head posture. Additionally, driving style information is also obtained through speed analysis and external traffic information. Finally, a fuzzy-based decision-making stage is proposed to manage both human cognitive information and driving style, and then limit the maximum allowed speed of a vehicle. The results showed that we were able to detect human cognitive parameters such as sleepiness –63% to 88% accuracy–, driver’s age –80% accuracy– and head posture –90.42% to 97.86% accuracy– as well as driving style –87.8% average accuracy. Based on such results, the fuzzy-based architecture was able to limit the maximum allowed speed for different scenarios, reducing it from 50 km/h to 17 km/h. Moreover, the fuzzy-based method showed to be more sensitive with respect to inputs changes than a previous published weighted-based inference method.     

The Nature of Physical Reality

This account of the dynamical theory of chaos leads to a metaphysical picture of a world with an open future, in which the laws of physics are emergent-downward approximations to a more subtle and supple reality and in which there is downward causation through information input as well as upward causation through energy input. Such a metaphysical picture can accommodate both human and divine agency.     

On the evaluation and application of different scales for quantifying pairwise comparisons in fuzzy sets

One of the most critical issues in many applications of fuzzy sets is the successful evaluation of membership values. A method based on pairwise comparisons provides an interesting way of evaluating membership values. That method was proposed by Saaty, almost 20 years ago, and since then has captured the interest of many researchers around the world. However, recent investigations reveal that the original scale may cause severe inconsistencies in many decision-making problems. Furthermore, exponential scales seem to be more natural for humans to use in many decision-making problems. In this paper two evaluative criteria are used to examine a total of 78 scales which can be derived from two widely used scales. The findings in this paper reveal that there is no single scale that can outperform all the other scales. Furthermore, the same findings indicate that a few scales are very efficient under certain conditions. Therefore, for a successful application of a pairwise-comparison-based method the appropriate scale needs to be selected and applied.