Granular Reasoning Using Zooming In & Out: Part 2. Aristotle's Categorical Syllogism

The concept of granular computing is applied to Aristotle's categorical syllogism. Such kind of reasoning is called granular reasoning in this paper. For the purpose, two operations called zooming in & out are introduced to reconstruct granules of possible worlds.     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

On a responsive replenishment system: a fuzzy logic approach

In today's competitive business environment, it is important that customers are able to obtain their preferred items in the shops they visit, particularly for convenience store chains such as 7–Eleven where popular items are expected to be readily available on the shelves of the stores for buyers. To minimize the cost of running such store chains, it is essential that stocks be kept to a minimum and at the same time large varieties of popular items are available for customers. In this respect, the replenishment system needs to be able to cope with the taxing demands of minimal inventory but at the same time keeping large varieties of needed items. This paper proposes a replenishment system which is able to respond to the fluctuating demands of customers and provide a timely supply of needed items in a cost–effective way. The proposed system embraces the principle of fuzzy logic which is able to deal with uncertainties by virtue of its fuzzy rules reasoning mechanism, thereby leveraging the responsiveness of the entire replenishment system for the chain stores. To validate the feasibility of the approach, a case study has been conducted in an emulated environment with promising results.     

Powers of observation in creative design

Being perceptive is a trait highly valued in scientific and engineering professions. What a scientist or engineer notices while considering a problem, evaluating alternatives, or interpreting data has a profound impact on how a problem is viewed and solved. This paper focuses on processes we believe underlie being perceptive: firstly, preparation—becoming attuned to salient or important features; secondly, assimilation-detection and exploration of patterns (invariants) as well as anomalies; and thirdly, strategic control-heuristic strategies for exploring the implications of what has been observed. These processes play an integral role in characteristic activities within creative design, including problem reformulation, the emergence of properties and constraints on the solution, and the ability to incorporate into the design experimental feedback from the environment and from experiences with prototypes and previous designs. The paper presents a computational model incorporating these ideas, implemented in a system called IMPROVISER.     

How to make and defend a proposal in a deliberation dialogue

In this paper it is shown how tools developed in argumentation theory and artificial intelligence can be applied to the development of a new dialectical analysis of the speech act of making a proposal in a deliberation dialogue. These tools are developed, modified and used to formulate dialogue pre-conditions, defining conditions and post-conditions for the speech act of making a proposal in a deliberation dialogue. The defining conditions set out what is required for a move in a dialogue to count as the making of a proposal by one of the parties. What is required are the conditions that (1) the move fit the requirements of the argumentation scheme for practical reasoning, and (2) the premises are propositions describing common goals of both parties or propositions that they reasonably consider means to achieve these goals. The analysis goes beyond the standard speech act approach by specifying not only the normative requirements for making a well-formed proposal, but also the requirements for responding to it by questioning or criticizing it, and the requirements for defending it.     

Branching and pruning: An optimal temporal POCL planner based on constraint programming

A key feature of modern optimal planners such as graphplan and blackbox is their ability to prune large parts of the search space. Previous Partial Order Causal Link (POCL) planners provide an alternative branching scheme but lacking comparable pruning mechanisms do not perform as well. In this paper, a domain-independent formulation of temporal planning based on Constraint Programming is introduced that successfully combines a POCL branching scheme with powerful and sound pruning rules. The key novelty in the formulation is the ability to reason about supports, precedences, and causal links involving actions that are not in the plan. Experiments over a wide range of benchmarks show that the resulting optimal temporal planner is much faster than current ones and is competitive with the best parallel planners in the special case in which actions have all the same duration.¹     

Overcoming intuition: Metacognitive difficulty activates analytic reasoning.

Humans appear to reason using two processing styles: System 1 processes that are quick, intuitive, and effortless and System 2 processes that are slow, analytical, and deliberate that occasionally correct the output of System 1. Four experiments suggest that System 2 processes are activated by metacognitive experiences of difficulty or disfluency during the process of reasoning. Incidental experiences of difficulty or disfluency--receiving information in a degraded font (Experiments 1 and 4), in difficult-to-read lettering (Experiment 2), or while furrowing one's brow (Experiment 3)--reduced the impact of heuristics and defaults in judgment (Experiments 1 and 3), reduced reliance on peripheral cues in persuasion (Experiment 2), and improved syllogistic reasoning (Experiment 4). Metacognitive experiences of difficulty or disfluency appear to serve as an alarm that activates analytic forms of reasoning that assess and sometimes correct the output of more intuitive forms of reasoning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

主动推送模式下的情报需求预测模型

针对主动推送模式下的情报需求预测问题,提出了基于案例推理的解决方案。设计了进行情报需求预测案例分析的工作流程,建立了案例属性描述模型;应用最近邻法进行案例的相似度评价,并通过信息增益的计算确定每个属性的权值,获得相似案例(集);提出了方案调整和推理策略。     

基于多模态推理图神经网络的场景文本视觉问答模型

文本阅读能力差和视觉推理能力不足是现有视觉问答(visual question answering, VQA)模型效果不好的主要原因,针对以上问题,设计了一个基于图神经网络的多模态推理(multi-modal reasoning graph neural network, MRGNN)模型。利用图像中多种形式的信息帮助理解场景文本内容,将场景文本图片分别预处理成视觉对象图和文本图的形式,并且在问题自注意力模块下过滤多余的信息;使用加入注意力的聚合器完善子图之间相互的节点特征,从而融合不同模态之间的信息,更新后的节点利用不同模态的上下文信息为答疑模块提供了更好的功能。在ST-VQA和TextVQA数据集上验证了有效性,实验结果表明,相比较此任务的一些其他模型,MRGNN模型在此任务上有明显的提升。