Quantified Propositional Logic and the Number of Lines of Tree-Like Proofs

There is an exponential speed-up in the number of lines of the quantified propositional sequent calculus over Substitution Frege Systems, if one considers proofs as trees. Whether this is true also for the number of symbols, is still an open problem. This revised version was published online in June 2006 with corrections to the Cover Date.     

A Note on Graded Modal Logic

We introduce a notion of bisimulation for graded modal logic. Using this notion, the model theory of graded modal logic can be developed in a uniform manner. We illustrate this by establishing the finite model property and proving invariance and definability results.     

Skepticism and Epistemic Logic

This essay attempts to implement epistemic logic through a non-classical inference relation. Given that relation, an account of '(the individual) a knows that A' is constructed as an unfamiliar non-normal modal logic. One advantage to this approach is a new analysis of the skeptical argument.     

Intuitionistic Propositional Logic without 'Contraction' but with 'Reductio'

Routley-Meyer type relational complete semantics are constructed for intuitionistic contractionless logic with reductio. Different negation completions of positive intuitionistic logic without contraction are treated in a systematical, unified and semantically complete setting.     

文化心理学的跨学科运用——以跨文化传播研究为例

文化心理学是最近二三十年来心理学中发展最快的领域之一,作为一门典型的交叉学科,它有人类学、心理学、传播学等多种学科取向,是一门有胸怀、有气度、能包容的学科。文化心理学与跨文化传播研究诞生在相同的社会历史文化背景中,拥有共同的学科渊源,这种天然的关系决定了跨文化传播研究中运用文化心理学的正当性、必然性。文化心理学的全球化研究视角为跨文化传播研究提供了参照; 文化的观念、文化适应理论、文化敏感性和文化冲突理论等文化心理学的概念和理论为跨文化传播研究提供了理论支撑; 文化心理学还为跨文化传播现象和问题的具体研究提供了分析工具。反之,跨文化传播研究不仅为文化心理学提供了鲜活的案例,还为其理论建构提供了重要资源。     

Metamorphic malicious code behavior detection using probabilistic inference methods

Existing antivirus programs detect malicious code based on fixed signatures; therefore, they have limitations in detecting metamorphic malicious code that lacks signature information or possesses circumventing code inserted into it. Research on the methods for detecting this type of metamorphic malicious code primarily focuses on techniques that can detect code based on behavioral similarity to known malicious code. However, these techniques measure the degree of similarity with existing malicious code using API function call patterns. Therefore, they have certain disadvantages, such as low accuracy and large detection times. In this paper, we propose a method which can overcome the limitations of existing methods by using the FP-Growth algorithm, a data mining technique, and the Markov Logic Networks algorithm, a probabilistic inference method. To perform a comparative evaluation of the proposed method's malicious code behavior detection, we performed inference experiments using malicious code with an inserted code for random malicious behavior. We performed experiments to select optimal weights for each inference rule to improve our malicious code behavior inferences’ accuracy. The results of experiments, in which we performed a comparative evaluation with the General Bayesian Network, showed that the proposed method had an 8% higher classification performance.     

Parameter selection based on fuzzy logic to improve UAV path-following algorithms

In order to steer an Unmanned Aerial Vehicle (UAV) and make it follow a desired trajectory, a high level controller is needed. Depending on the control algorithm, one or more parameters have to be tuned, having their values high impact on the performance. In most of the works, these parameters are taken as constant. In this paper, we apply fuzzy logic to select the parameters of the control law and compare this approach with the tuning by constant parameters and with another adjusting method based on the kinematic analysis of the equations of the UAV. After many simulations of the quadrotor following randomly generated paths, we have proved that the fuzzy tuning law is not only a good and feasible solution, but also more general as it can be applied to any trajectory.     

Disagreements Over Analogies

This essay presents a dialogical framework for treating philosophical disagreements as persuasion dialogues with analogical argumentation, with the aim of recasting philosophical disputes as disagreements over analogies. This has two benefits: (1) it allows us to temporarily bypass conflicting metaphysical intuitions by focusing on paradigmatic examples, (dis)similarities, and the plausibility of conclusions for or against a given point of view; and (2) it can reveal new avenues of argumentation regarding a given issue. This approach to philosophical disagreements is illustrated by studying the role of argumentation by analogy in disputes over Lockean justifications of intellectual property rights, and disagreements over whether artificial agents should be treated as moral agents. Finally, a nonexhaustive list of possible global and local points of contention over analogical arguments is identified in order to highlight potential avenues of argumentation in disagreements over analogies.     

The Generalized Quantum Episodic Memory Model

Recent evidence suggests that experienced events are often mapped to too many episodic states, including those that are logically or experimentally incompatible with one another. For example, episodic over‐distribution patterns show that the probability of accepting an item under different mutually exclusive conditions violates the disjunction rule. A related example, called subadditivity, occurs when the probability of accepting an item under mutually exclusive and exhaustive instruction conditions sums to a number >1. Both the over‐distribution effect and subadditivity have been widely observed in item and source‐memory paradigms. These phenomena are difficult to explain using standard memory frameworks, such as signal‐detection theory. A dual‐trace model called the over‐distribution (OD) model (Brainerd & Reyna, 2008) can explain the episodic over‐distribution effect, but not subadditivity. Our goal is to develop a model that can explain both effects. In this paper, we propose the Generalized Quantum Episodic Memory (GQEM) model, which extends the Quantum Episodic Memory (QEM) model developed by Brainerd, Wang, and Reyna (2013). We test GQEM by comparing it to the OD model using data from a novel item‐memory experiment and a previously published source‐memory experiment (Kellen, Singmann, & Klauer, 2014) examining the over‐distribution effect. Using the best‐fit parameters from the over‐distribution experiments, we conclude by showing that the GQEM model can also account for subadditivity. Overall these results add to a growing body of evidence suggesting that quantum probability theory is a valuable tool in modeling recognition memory.     

The four antinomies of the death instinct1

Matte Blanco examines four paradoxical positions that arise out of Freud's writings on the death instinct. He notes that death is not a content known to the unconscious. Furthermore, the absence of time and space in the unconscious means that the conditions necessary for any process such as instinct are similarly absent. Matte Blanco demonstrates the way in which the antinomies that he explores can be explained in terms of the logics that obtain in the unconscious, and he suggests that the concept of the death instinct is one of the most profound expressions of the relationship between the modes that underlie conscious and unconscious logic.