Cognitive architectures as Lakatosian research programmes: two case studies

Cognitive architectures - task-general theories of the structure and function of the complete cognitive system - are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he failed to demonstrate that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility

Interaction with text : a study of teachers' mediation of materials in mainstream and ESOL secondary school classrooms : a thesis presented in fulfilment of the requirements for the degree of Master of Arts in Second Language Teaching at Massey University

The increasingly multi-cultural nature of New Zealand society is accompanied by burgeoning school enrolments of students whose first language is not English (called ESOL students in this study). Immigration, refugee movements, and the recruitment of international students for largely economic purposes, all contribute to this. Whilst many of these students are competent English speakers when they enrol at our schools, large numbers are not. In secondary schools, regardless of English language competence, most ESOL students are placed in mainstream classes for the majority of their timetable, with the addition of a relatively small amount of specialist English language tuition. How do both these mainstream and ESOL teachers address the language learning needs of these students? Because texts remain central to classroom teaching and learning, this study considers how teachers mediate texts with students. It has a particular focus on how this mediation contributes to the language learning environment for ESOL students in both mainstream and ESOL classes, using classroom observation as its primary source of data. This study reveals both predictable and unexpected results. It is not surprising that it finds extensive use of questioning by teachers in their mediation of texts. However, the value of copious recall or display questions for senior secondary school students is challenged by this study, and the importance is asserted of referential questioning to develop critical thinking skills in relation to text. The preponderance of teacher-dominated classrooms and classroom language is a disappointing finding of this study, especially because the study reveals that students say very little in such an environment. More collaborative and interactive teaching methods would help ESOL students use, and therefore learn, English more effectively. Thus the study finds a lot of class time invested in the use of texts, but comparatively little effective mediation to help both native-speaking and ESOL students comprehend the language of the texts. The study reveals the need for teachers to acknowledge their role as teachers of language, and especially to mediate texts with students by teaching reading strategies

Evaluation of Cognitive Architectures for Cyber-Physical Production Systems

Cyber-physical production systems (CPPS) integrate physical and computational resources due to increasingly available sensors and processing power. This enables the usage of data, to create additional benefit, such as condition monitoring or optimization. These capabilities can lead to cognition, such that the system is able to adapt independently to changing circumstances by learning from additional sensors information. Developing a reference architecture for the design of CPPS and standardization of machines and software interfaces is crucial to enable compatibility of data usage between different machine models and vendors. This paper analysis existing reference architecture regarding their cognitive abilities, based on requirements that are derived from three different use cases. The results from the evaluation of the reference architectures, which include two instances that stem from the field of cognitive science, reveal a gap in the applicability of the architectures regarding the generalizability and the level of abstraction. While reference architectures from the field of automation are suitable to address use case specific requirements, and do not address the general requirements, especially w.r.t. adaptability, the examples from the field of cognitive science are well usable to reach a high level of adaption and cognition. It is desirable to merge advantages of both classes of architectures to address challenges in the field of CPPS in Industrie 4.0

Cognitive Structures of Good and Poor Novice Problem Solvers in Physics

The way knowledge is organized in memory is generally expected to relate to the degree of success in problem solving. In the present study, we investigated whether good novice problem solvers have their knowledge arranged around problem types to a greater extent than poor problem solvers have. In the subject of physics (electricity and magnetism), 12 problem types were distinguished according to their underlying physics principles. For each problem type, a set of elements of knowledge containing characteristics of the problem situation, declarative knowledge, and procedural knowledge was constructed. All of the resulting 65 elements were printed on cards, and first-year university students in physics ( N = 47) were asked to sort these cards into coherent piles shortly after they had taken an examination on electricity and magnetism. Essentially, good novice problem solvers sorted the cards according to problem types; the sorting by the poor problem solvers seemed to be determined to a greater extent by the surface characteristics of the elements. We concluded than an organization of knowledge around problem types might be highly conducive to good performance in problem solving by novice problem solvers

Modelling dynamic decision making with the ACT-R cognitive architecture

This paper describes a model of dynamic decision making in the Dynamic Stocks and Flows (DSF) task, developed using the ACT-R cognitive architecture. This task is a simple simulation of a water tank in which the water level must be kept constant whilst the inflow and outflow changes at varying rates. The basic functions of the model are based around three steps. Firstly, the model predicts the water level in the next cycle by adding the current water level to the predicted net inflow of water. Secondly, based on this projection, the net outflow of the water is adjusted to bring the water level back to the target. Thirdly, the predicted net inflow of water is adjusted to improve its accuracy in the future. If the prediction has overestimated net inflow then it is reduced, if it has underestimated net inflow it is increased. The model was entered into a model comparison competition-the Dynamic Stocks and Flows Challenge-to model human performance on four conditions of the DSF task and then subject the model to testing on five unseen transfer conditions. The model reproduced the main features of the development data reasonably well but did not reproduce human performance well under the transfer conditions. This suggests that the principles underlying human performance across the different conditions differ considerably despite their apparent similarity. Further lessons for the future development of our model and model comparison challenges are considered

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

Bridging the Gap Between Declarative and Procedural Knowledge in the Training of Translators: Meta-Reflection Under Scrutiny

Aiming at reassessing the declarative/procedural knowledge dichotomy in the training of translators, this article builds on connectionist principles (Elman et al. 1996) and Relevance Theory (Sperber & Wilson 1986/1995) to present the rationale for a project which, from a pro-active standpoint, suggests that translator’s training could incorporate some of the methodologies used for data elicitation in translation process studies and apply them in classroom settings as an avenue to increase the level of awareness among novice translators. Meta-reflection, according to the article, is the key to promote awareness-raising and, as a consequence, an increment in the quality of translator.s training.Ayant pour but une réévaluation de la dichotomie entre connaissance déclarative et procédurale dans l’enseignement et l’apprentissage de la traduction, cet article utilise les principes connectionistes (Elman et al. 1996) de la théorie de la pertinence (Sperber & Wilson 1986/1995) pour présenter le design d’un projet qui, d’une perspective proactive, se propose d’utiliser les méthodologies des recherches sur le processus de la traduction et les mettre en service dans la classe de traduction pour accroître le niveau de conscience parmi les jeunes traducteurs. Selon cet article, la méta-réflexion est la clef pour fournir à ces jeunes traducteurs un accroissement de leurs activités conscientes et pour améliorer la formation de traducteurs