• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.47-75
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• 2010

Two experiments were conducted to explore whether the Or structure works as a default causal model in inferring the causal structure from the contingency data. The contingencies of three unfamiliar variables were used in Experiment 1. Participants inferred the Or structure quite well from the OR data, but incorrectly inferred the Or structure from the And data for about a little less than half of the time, and almost always inferred the Or structure from the chain data. The results suggested that the Or interpretation can be the default causal model. The prevalence of the Or interpretation from the contingency data was reported even when the three variables were familiar ones in Experiment 2. Multinomial modeling performed on the results of the two experiments strongly suggested that the Or interpretation work as a default causal model.

• Proceedings of the Korean System Dynamics Society
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• 2000.02a
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• pp.39-60
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• 2000

시스템 다이내믹스 모델링은 시스템의 인과 구조를 파악하기 위한 인과지도 분석과 인과 구조를 시뮬레이션하기 위한 저량/유량 모텔링으로 이분화 된다고 할 수 있다. 일반적으로 시스템 다이내믹스 모델링에서 인과지도는 저량/유량 모델링의 기반이 되어 왔다. 그러나 인과지도가 지나치게 추상화되어 있는 경우, 인과지도로부터 저량/유량 모델을 구축하는 것은 상당히 어려운 작업이었다. 특히 정책결정자의 주관을 표현한 인지지도를 저량/유량 모델로 전환하는 데에는 연구자의 주관이 첨가됨으로써 인지지도의 특성을 상실시킬 위험이 있었다. 본 논문에서는 인지지도 또는 추상적인 인과지도를 저량/유량 모델로 전환시키는 방법으로써 NUMBER(Normalized Unit Modelling By Elementary Relationships)에 관하여 논의하고자 한다. 본 논문에서 제안된 NUMBER 방법을 활용하여 김대중 대통령의 금융위기 극복 정책에 관한 인지지도를 저량/유량 모델로 전환하여 시뮬레이션 하여 봄으로써, 연구자의 주관을 최소화하면서 정책결정자의 인지지도나 추상적인 인과지도를 간편하게 저량/유량 모델로 전환시켜 그 동태적 행태를 분석할 수 있다는 점을 제안하고자 한다.

• Korean Journal of Logic
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• v.20 no.1
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• pp.21-67
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• 2017

In this paper, I critically examine Sartorio's (2006) argument for disjunctive cause, and put forth disjunctive causal structure in a different way. I show that the disjunctive causal structure meets not just what Sartorio means to claim but also our understanding of causal responsibility. First, I introduce Sartorio's argument for disjunctive cause. Second, I critically discuss Sartorio's responses to the criticisms of her arguments for disjunctive cause, and propose another problem with her arguments. Finally, I explicate in a different way Sartorio's disjunctive cause in terms of disjunctive causal structure founded on moderate variables, causal interaction, and probability trajectory. I notice, regarding the disjunctive causal structure, the role of causal interaction of cause events with moderate variables. I reveal, regarding the disjunctive causal structure, the significance of indetermination of cause events and effect events for our understanding of causal responsibility. I show that the disjunctive causal structure guides us more convincingly to assign causal responsibility to an agent. I come to three conclusions. First, there is no disjunctive cause event Sartorio argues for. Second, propensities of events to be causally connected to an effect event constitute disjunctive relation. Third, we should notice indetermination of cause events and effect events while assigning causal responsibility to an agent.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.164-168
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• 1999

HLA(High Level Architecture)는 분산 시뮬레이션의 표준화를 위한 개념적인 분산 시스템 프레임워크이며, RTI(Run Time Infrastructure)는 HLA를 따르는 분산 시뮬레이션들을 위한 네트워크 하부구조이다. 분산 시뮬레이션은 분산 노드간에 효율적이고 인과 오류가 없는 통신 방법의 지원이 필수적이며, RTI는 시뮬레이션에 참여하는 분산 노드간 메시지 전송을 위하여 최선(best-effort) 전송 서비스와 신뢰(reliable) 전송 서비스를 규정하고 있다. RTI의 메시지 전송 서비스는 기본적으로 메시지 전송 과정에서 메시기간 인과 관계를 유지해야 하는 다자간 통신 서비스이며, 본 논문에서는 인터넷상에서 인과 오류가 없는 다자간 통신을 위한 새로운 형식의 분산 시스템 구조를 제안하고, 성능 평가를 위한 실험 결과를 소개한다.

• Korean Journal of Logic
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• v.18 no.1
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• pp.83-133
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• 2015

In this paper, I pose a problem for Hitchcock's arguments for two concepts of effects that are intended to explicate double causal effects, and put forth a theory that is intended not just to meet the problem but also to accommodate Hitchcock's theory and Eells' theory both. First, I introduce an example of dual causal effects, and examine the accounts of Otte(1985) and Eells(1987) on how to explicate the dual effects. I show that their accounts of the dual effects help us understand the problem of dual effects and see how different it is for Cartwright(1979, 1989, 1995), Eells(1991, 1995), and Hitchcock(2001a) to meet the problem. Second, I introduce two concepts of effects on Hitchcock(2001a), that is, net effect and component effect that are allegedly analogous to two effects of structural equation model. Third, I reveal the significance of homogeneous subpopulation and causal interaction regarding the problem of dual effects while examining Cartwright's theory and Elles' theory. Fourth, I critically examine the two concepts of effects on Hitchcock and argue against Hitchcock's criticism of Eells' theory. Fifth, I take a moderator variable of structural equation model and a moderator effect into the probabilistic theory of causality, and formally generalize causal interaction due to the dual effects in terms of disjunctive relation and counterfactual conditionals. I expect my account of disjunctive relation and counterfactual conditionals to contribute not just to several problems the received theories of causal modelling confront but also to the structural equation models many people exploit as a promising statistical methodology.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.59-72
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• 2021

Concepts and categories offer the basis for inference pertaining to unobserved features. Prior research on category-based induction that used blank properties has suggested that similarity between categories and features explains feature inference (Rips, 1975; Osherson et al., 1990). However, it was shown by later research that prior knowledge had a large influence on category-based inference and cases were reported where similarity effects completely disappeared. Thus, this study tested category-based feature inference when features are connected in a causal chain and proposed a feature inference model that predicts participants' inference ratings. Each participant learned a category with four features connected in a causal chain and then performed feature inference tasks for an unobserved feature in various exemplars of the category. The results revealed nonindependence, that is, the features not only linked directly to the target feature but also to those screened-off by other feature nodes and affected feature inference (a violation of the causal Markov condition). Feature inference model of causal model theory (Sloman, 2005) explained nonindependence by predicting the effects of directly linked features and indirectly related features. Indirect features equally affected participants' inference regardless of causal distance, and the model predicted smaller effects regarding causally distant features.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.2
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• pp.72-83
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• 2003

The main purpose of this study was to analyze the causal relationship, in the perspective of Total Quality Management, among the education quality factors, which were suggested in the previous researches, including education leadership, process improvement, educational environment, regional commitment, student performance and satisfaction of education quality. In this study, education quality factors were measured by several measures, and were processed with the most efficient statistical package in the SEM area, AMOS. In order to analyze the causal relationship among the education quality, this study designed the structural equation model with suggested factors and established several the research hypotheses. Also this study found that there was a prominent causality among the education quality factors, such as education leadership, education environment, student performance and satisfaction of education quality.

• Korean Journal of Logic
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• v.12 no.1
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• pp.25-43
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• 2009

이 논문은 유형 유물론의 인과적 논변과 양립할 수 있는 합리적 인과성, 곧 주관적 인과성의 한 존재론을 주장한다. 의욕들과 결심들 같은 의지적 마음은 능동적이다. 반면에, 욕망들과 믿음들 같은 정서적 인지적 마음은 수동적이다. 의지는 욕망과 믿음의 단순한 법칙적 결과가 아니다. 행위자가 개입한 합리적 결과이다. 따라서 의지 상태는 인과적 유형화를 갖지 못하므로 물리적으로 환원될 길이 없어 보인다. 구조적인 기초원자들이 연합해 움직이는 어떤 원자 모임을 행위자로 본다면, 행위자 원인은 하향적 인과를 함축하지 않는다. 그리고 유형 유물론 논변은 환원주의를 함축하지 않는다. 환원주의는 개념적 정의를 추가로 요구하기 때문이다. 따라서 인과의 주관적 개념, 행위자 개념이 유형 유물론을 배제하지 않는다.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.33-55
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• 1995

포지인식도(Fuzzy Cognitive Map : FCM)는 추상적이고 비구조적이며 동적인 응용영역에서 전문가의 인과관계 지식(causal knowledge)을 표현하는데 매우 유용한 도구이다. FCM이 기존의 다른 네트워크 형태의 지식표현방법과 다른 차이점은 대상 문제의 개념변수들을 퍼지집합으로 묘사하고, 개념 변수간의 관계를 퍼지 인과관계로 다룬다는 것이다. 그런데 FCM의 특성이 아직 충분히 논의되지 않은 상태에서는 FCM의 적용에 있어 오류가 일어날 수 있다. 본 논문의 목적은 첫째, FCM의 특성과 의미를 보다 명확히 하여 이론적인 측면을 보강하고자 한다. 이를 위해 논리적관계(implication)와는 다른 인과관계의 정의를 다시 확인하고, 이정의에 기초한 퍼지 인과관계의 특성을 파악하고, 퍼지 인과관계와 대비되는 퍼지 부분인과관계 및 단방향 개념변수를 새로이 정의함으로써 FCM구축에 있어 잘못된 이해가 없게 하며, 둘째, FCM에서는 추론 방식이 갖추어야 할 원칙을 명시하고 이에 따라 이러한 원칙을 준수하는 새로운 추론 방식을 제시한다.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.147-158
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• 2008

Fuzzy Cognitive Map (FCM) and Bayesian Belief Network (BBN) are two major frameworks for modeling, representing and reasoning about causal knowledge. Despite their extensive use in causal knowledge engineering, there is no reported work which compares their respective roles. This paper aims to fill the gap by providing a qualitative comparison of the two frameworks through a systematic analysis based on some inherent features of the frameworks. We proposed a set of comparison criteria which covers the entire process of causal knowledge engineering, including modeling, representation, and reasoning. These criteria are usability, expressiveness, reasoning capability, formality, and soundness. The results of comparison have revealed some important facts about the characteristics of FCM and BBN, which will help to determine how FCM and BBN should be used, with respect to each other, in causal knowledge engineering.