A logical expression of reasoning

A non-monotonic logic, the Logic of Plausible Reasoning (LPR), capable of coping with the demands of what we call complex reasoning, is introduced. It is argued that creative complex reasoning is the way of reasoning required in many instances of scientific thought, professional practice and common life decision taking. For managing the simultaneous consideration of multiple scenarios inherent in these activities, two new modalities, weak and strong plausibility, are introduced as part of the Logic of Plausible Deduction (LPD), a deductive logic specially designed to serve as the monotonic support for LPR. Axiomatics and semantics for LPD, together with a completeness proof, are provided. Once LPD has been given, LPR may be defined via a concept of extension over LPD. Although the construction of LPR extensions is first presented in standard style, for the sake of comparison with existing non-monotonic formalisms, alternative more elegant and intuitive ways for constructing non-monotonic LPR extensions are also given and proofs of their equivalence are presented.     

A general method for proving decidability of intuitionistic modal logics

We generalise the result of [H. Ganzinger, C. Meyer, M. Veanes, The two-variable guarded fragment with transitive relations, in: Proc. 14th IEEE Symposium on Logic in Computer Science, IEEE Computer Society Press, 1999, pp. 24–34] on decidability of the two variable monadic guarded fragment of first order logic with constraints on the guard relations expressible in monadic second order logic. In [H. Ganzinger, C. Meyer, M. Veanes, The two-variable guarded fragment with transitive relations, in: Proc. 14th IEEE Symposium on Logic in Computer Science, IEEE Computer Society Press, 1999, pp. 24–34], such constraints apply to one relation at a time. We modify their proof to obtain decidability for constraints involving several relations. Now we can use this result to prove decidability of multi-modal modal logics where conditions on accessibility relations involve more than one relation. Our main application is intuitionistic modal logic, where the intuitionistic and modal accessibility relations usually interact in a non-trivial way.     

A general tableau method for propositional interval temporal logics: Theory and implementation

In this paper, we focus our attention on tableau methods for propositional interval temporal logics. These logics provide a natural framework for representing and reasoning about temporal properties in several areas of computer science. However, while various tableau methods have been developed for linear and branching time point-based temporal logics, not much work has been done on tableau methods for interval-based ones. We develop a general tableau method for Venema's CDT logic interpreted over partial orders (BCDT⁺ for short). It combines features of the classical tableau method for first-order logic with those of explicit tableau methods for modal logics with constraint label management, and it can be easily tailored to most propositional interval temporal logics proposed in the literature. We prove its soundness and completeness, and we show how it has been implemented.     

A Sound and Complete Tableau Calculus for Reasoning about only Knowing and Knowing at Most

We define a tableau calculus for the logic of only knowing and knowing at most ON, which is an extension of Levesque's logic of only knowing O. The method is based on the possible-world semantics of the logic ON, and can be considered as an extension of known tableau calculi for modal logic K45. From the technical viewpoint, the main features of such an extension are the explicit representation of "unreachable" worlds in the tableau, and an additional branch closure condition implementing the property that each world must be either reachable or unreachable. The calculus allows for establishing the computational complexity of reasoning about only knowing and knowing at most. Moreover, we prove that the method matches the worst-case complexity lower bound of the satisfiability problem for both ON and O. With respect to [22], in which the tableau calculus was originally presented, in this paper we both provide a formal proof of soundness and completeness of the calculus, and prove the complexity results for the logic ON.     

A procedural theory of eye movements in doing arithmetic

A procedural theory of eye movement that accounts for main features of the stochastic behavior of eye-fixation durations and direction of movement of saccades in the process of solving arithmetic exercises of addition and subtraction is presented. The best-fitting distribution of fixation durations with a relatively simple theoretical justification consists of a mixture of an exponential distribution and the convolution of two exponential distributions. The eye movements themselves were found to approximate a random walk that fits rather closely in both adult and juvenile subjects the motion postulated by the normative algorithm ordinarily taught in schools. Certain structural features of addition and subtraction exercises, such as the number of columns, the presence or absence of a carry or a borrow, are well known to affect their difficulty. In this study, regressions on such structural variables were found to account for only a relatively small part of the variation in eye-fixation durations.     

Diagnostic models for procedural bugs in basic mathematical skills

A new diagnostic modeling system for automatically synthesizing a deep-structure model of a student's misconceptions or bugs in his basic mathematical skills provides a mechanism for explaining why a student is making a mistake as opposed to simply identifying the mistake. This report is divided into four sections: The first provides examples of the problems that must be handled by a diagnostic model. It then introduces procedural networks as a general framework for representing the knowledge underlying a skill. The challenge in designing this representation is to find one that facilitates the discovery of misconceptions or bugs existing in a particular student's encoding of this knowledge. The second section discusses some of the pedagogical issues that have emerged from the use of diagnostic models within an instructional system. This discussion is framed in the context of a computer-based tutoring/gaming system developed to teach students and student teachers how to diagnose bugs strategically as well as how to provide a better understanding of the underlying structure of arithmetic skills. The third section describes our uses of an executable network as a tool for automatically diagnosing student behavior, for automatically generating “diagnostic” tests, and for judging the diagnostic quality of a given exam. Included in this section is a discussion of the success of this system in diagnosing 1300 school students from a data base of 20.000 test items. The last section discusses future research directions.     

Adaptive non-interventional heuristics for covariation detection in causal induction: model comparison and rational analysis

In this article, 41 models of covariation detection from 2 × 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi-coefficient under an extreme rarity assumption, which has been shown to be an important factor in covariation detection (McKenzie & Mikkelsen, 2007) and data selection (Hattori, 2002; Oaksford & Chater, 1994, 2003). The results were supportive of the new model. To investigate its explanatory adequacy, a rational analysis using two computer simulations was conducted. These simulations revealed the environmental conditions and the memory restrictions under which the new model best approximates the normative model of covariation detection in these tasks. They thus demonstrated the adaptive rationality of the new model.     

A criterion for determining the optimum value of twist in the topological model

In previous works, in which the topological model has been applied to martensitic phase transformations, the value of twist angle ω was determined based on the habit plane-(HP) matching method, where the physical realization of the so-predicted interfacial defect networks may require reorientations of defect line directions by short-range diffusion, though no long-range diffusion was needed. In the present work, a novel criterion for determining the optimum value of twist is proposed so that the predicted interface defects are not only able to fulfil the function of fully accommodating the coherency strains arising on the terrace plane, but also capable of reaching the required position at the HP without long- or short-range diffusions. A numerical analysis for an Fe–20Ni–5Mn alloy is demonstrated based on the newly proposed criterion, and the predictions so obtained are in good agreement with the results provided by the phenomenological theory and experimental measurements.     

Rational Comprehension of Arguments in Theoretical Texts: A Program for an Argumentative-Linguistic Approach

A method of linguistically-oriented reasoning comprehension is proposed. It is based on semiological principles of text comprehension. Both content and form are essential for comprehending argumentative texts. A text recipient is viewed as a rational judge trying to detect all the components of the argument he/she considers and thus to see if the argument is consistent. Elementary and higher level argumentative units of the text are discovered by applying a modified S. Toulmin's model of argumentative functions. Validity and correctness of arguments are established by means of a new – linguistic – interpretation of traditional syllogistic.     

Beyond subgoaling: A dynamic knowledge generation framework for creative problem solving in cognitive architectures

In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures.     

中学生厌学心理及其干预与学习效率的相关研究

本研究旨在考察两个问题：1．心理咨询是否是改变中学生厌学心理的有效途径,如果是,它能够在多大程度上改变厌学心理;2．厌学心理的改善能否有效提高中学生学习效率。本实验用问卷调查法从183名中学生中筛选出有厌学心理的学生24名。运用个体心理咨询、团体心理咨询等手段对这24名学生进行为期4个月干预、结果表明：心理咨询能够有效且明显地改善厌学心理。但要完全消除厌学心理则还需要辅以其他干预手段;随着学生厌学心理的改善,其学习效率也相应有了明显的提高。     

A Bayesian-optimal principle for learner-friendly adaptation in learning games

Adaptive learning games should provide opportunities for the student to learn as well as motivate playing until goals have been reached. In this paper, we give a mathematically rigorous treatment of the problem in the framework of Bayesian decision theory. To quantify the opportunities for learning, we assume that the learning tasks that yield the most information about the current skills of the student, while being desirable for measurement in their own right, would also be among those that are efficient for learning. Indeed, optimization of the expected information gain appears to naturally avoid tasks that are exceedingly demanding or exceedingly easy as their results are predictable and thus uninformative. Still, tasks that are efficient for learning may be experienced as too challenging, and the resulting failures can lower motivation. Therefore, in addition to quantifying the expected informational benefit for learning of any prospective task to be presented next, we also model the expected motivational cost of its presentation, measured simply as the estimated probability of failure in our example model. We propose a “learner-friendly” adaptation algorithm that chooses the learning tasks by optimizing the expected benefit divided by the expected cost. We apply this algorithm to a Rasch-like student model implemented within a real-world application and present initial results of a pilot experiment.     

Assigning Integration: A Framework for Intellectual,Personal, and Professional Development in Seminary Courses

This article explores assignments as a core teaching practice essential to integrating the cognitive, personal, and professional identities of seminary students. These core practices emerge in seminary curricula where there is a strong focus on the teaching of canonical texts and a goal of achieving textual mastery. We propose that carefully chosen and constructive assignments achieve the kind of integration necessary for building content knowledge and the professional, spiritual, and religious identities of our students. While the difference between the educational goals of clergy‐training in a seminary and training graduate students in the academy can be sharp, we argue here for ways to make that contrast both productive and generative.     

Interpersonal comparison versus persuasive argumentation: A more direct test of alternative explanations for group-induced shifts in individual choice

One class of theories explains group induced shifts in individual choice in terms of interpersonal comparison process. By comparing himself with others a member finds out that his position is uncomfortably discrepant, e.g., he is overly “cautious” or overly “risky”. Knowledge of this discrepancy presumably is necessary and sufficient to induce him to change his initial choice. Another class of theories holds that merely knowing one is different from others is unimportant. Shifts in choice occur because during discussion a member is exposed to persuasive arguments which prior to discussion were not available to him. Thus, if in a factorial design one independently varied (a) the number of others' choices available for comparison and (b) the number of arguments others presented in support of these choices, interpersonal comparison theories would predict the magnitude of the shift to be a function of (a) and not of (b), while theories of persuasive argumentation would predict the opposite. When such an experiment was performed the only reliable main effects were based on the number of arguments, (b), as predicted by persuasive arguments. In no instance did effects involving (a) approach significance.     

How Do I Treat My Hungry Lion: A Model for Violence Management in Prison

This theoretical model for the management of violence relies on the notion that there are fundamentally only two kinds of prison violence—provoked and unprovoked—and that all violence is caused by the influence of some fear-causing agent which triggers the autonomic nervous system's Fight or Flight Response (FFR) which in turn causes the release of FFR chemicals to create and enable an action potential for violence in the actor. Provoked violence is an act of violence which occurs in response to an FFR instigated by some external, independent contemporaneous, real or imagined fear causing agent. Treating provoked violence must include suppressing the production of an excess of FFR stimulant chemicals, which at the same time employing psychodynamic therapy to modify the negative behavior learned from a lifetime of excessive responses to FFR chemical releases. Unprovoked violence is the result of an actor's addiction to FFR chemicals. This addiction leads the actor to experience an apperceptive compulsion to engage in thrill seeking as a method of exposing himself to fear causing agents that are calculated to cause the release of FFR chemicals. In order to treat unprovoked violence you must treat both the chemical addiction and the negative pattern of behavior which was learned to support the habit of self-triggering an FFR. Thus any successful treatment of violence must employ both energetic and psychodynamic models for development of fear management strategies.