Specialization of the rostral prefrontal cortex for distinct analogy processes

Analogical reasoning is central to learning and abstract thinking. It involves using a more familiar situation (source) to make inferences about a less familiar situation (target). According to the predominant cognitive models, analogical reasoning includes 1) generation of structured mental representations and 2) mapping based on structural similarities between them. This study used functional magnetic resonance imaging to specify the role of rostral prefrontal cortex (PFC) in these distinct processes. An experimental paradigm was designed that enabled differentiation between these processes, by temporal separation of the presentation of the source and the target. Within rostral PFC, a lateral subregion was activated by analogy task both during study of the source (before the source could be compared with a target) and when the target appeared. This may suggest that this subregion supports fundamental analogy processes such as generating structured representations of stimuli but is not specific to one particular processing stage. By contrast, a dorsomedial subregion of rostral PFC showed an interaction between task (analogy vs. control) and period (more activated when the target appeared). We propose that this region is involved in comparison or mapping processes. These results add to the growing evidence for functional differentiation between rostral PFC subregions

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations

Computational and Biological Analogies for Understanding Fine-Tuned Parameters in Physics

In this philosophical paper, we explore computational and biological analogies to address the fine-tuning problem in cosmology. We first clarify what it means for physical constants or initial conditions to be fine-tuned. We review important distinctions such as the dimensionless and dimensional physical constants, and the classification of constants proposed by Levy-Leblond. Then we explore how two great analogies, computational and biological, can give new insights into our problem. This paper includes a preliminary study to examine the two analogies. Importantly, analogies are both useful and fundamental cognitive tools, but can also be misused or misinterpreted. The idea that our universe might be modelled as a computational entity is analysed, and we discuss the distinction between physical laws and initial conditions using algorithmic information theory. Smolin introduced the theory of "Cosmological Natural Selection" with a biological analogy in mind. We examine an extension of this analogy involving intelligent life. We discuss if and how this extension could be legitimated. Keywords: origin of the universe, fine-tuning, physical constants, initial conditions, computational universe, biological universe, role of intelligent life, cosmological natural selection, cosmological artificial selection, artificial cosmogenesis.Comment: 25 pages, Foundations of Science, in pres

The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

Problems with Using Evolutionary Theory in Philosophy

Does science move toward truths? Are present scientific theories (approximately) true? Should we invoke truths to explain the success of science? Do our cognitive faculties track truths? Some philosophers say yes, while others say no, to these questions. Interestingly, both groups use the same scientific theory, viz., evolutionary theory, to defend their positions. I argue that it begs the question for the former group to do so because their positive answers imply that evolutionary theory is warranted, whereas it is self-defeating for the latter group to do so because their negative answers imply that evolutionary theory is unwarranted

Space is the machine, part four: theoretical syntheses

Part IV of the book, ‘Theoretical Syntheses’, begins to draw together some of the questions raised in Part I, the regularities shown in Part II and the laws proposed in Part III, to suggest how the two central problems in architectural theory, namely the form-function problem and the form-meaning problem, can be reconceptualised. Chapter 10, ‘Space is the machine’, reviews the form-function theory in architecture and attempts to establish a pathology of its formulation: how it came to be set up in such a way that it could not be solved. It then proposes how the configuration paradigm permits a reformulation, through which we can not only make sense of the relation between form and function in buildings, but also we can make sense of how and why buildings, in a powerful sense are ‘social objects’ and in fact play a powerful role in the realisation and sustaining of human society. Finally, in Chapter 11, ‘The reasoning art’, the notion of configuration is applied to the study of what architects do, that is, design. Previous models of the design process are reviewed, and it is shown that without knowledge of configuration and the concept of the non-discursive, we cannot understand the internalities of the design process. A new knowledge-based model of design is proposed, with configuration at its centre. It is argued from this that because design is a configurational process, and because it is the characteristic of configuration that local changes make global differences, design is necessarily a top down process. This does not mean that it cannot be analysed, or supported by research. It shows however that only configurationally biased knowledge can really support the design Introduction Space is the machine | Bill Hillier Space Syntax Introduction process, and this, essentially, is theoretical knowledge. It follows from this that attempts to support designers by building methods and systems for bottom up construction of designs must eventually fail as explanatory systems. They can serve to create specific architectural identities, but not to advance general architectural understanding. In pursuing an analytic rather than a normative theory of architecture, the book might be thought by some to have pretensions to make the art of architecture into a science. This is not what is intended. One effect of a better scientific understanding of architecture is to show that although architecture as a phenomenon is capable of considerable scientific understanding, this does not mean that as a practice architecture is not an art. On the contrary, it shows quite clearly why it is an art and what the nature and limits of that art are. Architecture is an art because, although in key respects its forms can be analysed and understood by scientific means, its forms can only be prescribed by scientific means in a very restricted sense. Architecture is law governed but it is not determinate. What is governed by the laws is not the form of individual buildings but the field of possibility within which the choice of form is made. This means that the impact of these laws on the passage from problem statement to solution is not direct but indirect. It lies deep in the spatial and physical forms of buildings, in their genotypes, not their phenotypes. Architecture is therefore not part art, and part science, in the sense that it has both technical and aesthetic aspects, but is both art and science in the sense that it requires both the processes of abstraction by which we know science and the processes of concretion by which we know art. The architect as scientist and as theorist seeks to establish the laws of the spatial and formal materials with which the architect as artist then composes. The greater scientific content of architecture over art is simply a function of the far greater complexity of the raw materials of space and form, and their far greater reverberations for other aspects of life, than any materials that an artist uses. It is the fact that the architect designs with the spatial stuff of living that builds the science of architecture into the art of architecture. It may seem curious to argue that the quest for a scientific understanding of architecture does not lead to the conclusion that architecture is a science, but nevertheless it is the case. In the last analysis, architectural theory is a matter of understanding architecture as a system of possibilities, and how these are restricted by laws which link this system of possibilities to the spatial potentialities of human life. At this level, and perhaps only at this level, architecture is analogous to language. Language is often naïvely conceptualised as a set of words and meanings, set out in a dictionary, and syntactic rules by which they may be combined into meaningful sentences, set out in grammars. This is not what language is, and the laws that govern language are not of this kind. This can be seen from the simple fact that if we take the words of the dictionary and combine them in grammatically correct sentences, virtually all are utterly meaningless and do not count as legitimate sentences. The structures of language are the laws which restrict the combinatorial possibilities of words, and through these restrictions construct the sayable and the meaningful. The laws of language do not therefore tell us what to say, but prescribe the structure and limits of the sayable. It is within these limits that we use language as the prime means to our individuality and creativity. In this sense architecture does resemble language. The laws of the field of architecture do not tell designers what to do. By restricting and structuring the field of combinatorial possibility, they prescribe the limits within which architecture is possible. As with language, what is left from this restrictive structuring is rich beyond imagination. Even so, without these laws buildings would not be human products, any more than meaningless but syntactically correct concatenations of words are human sentences. The case for a theoretical understanding of architecture then rests eventually not on aspiration to philosophical or scientific status, but on the nature of architecture itself. The foundational proposition of the book is that architecture is an inherently theoretical subject. The very act of building raises issues about the relations of the form of the material world and the way in which we live in it which (as any archaeologist knows who has tried to puzzle out a culture from material remains) are unavoidably both philosophical and scientific. Architecture is the most everyday, the most enveloping, the largest and the most culturally determined human artefact. The act of building implies the transmission of cultural conventions answering these questions through custom and habit. Architecture is their rendering explicit, and their transmutation into a realm of innovation and, at its best, of art. In a sense, architecture is abstract thought applied to building, even therefore in a sense theory applied to building. This is why, in the end, architecture must have analytic theories

Learning strategies in interpreting text: From comprehension to illustration

Learning strategies can be described as behaviours and thoughts a learner engages in during learning that are aimed at gaining knowledge. Learners are, to use Mayer’s (1996) constructivist definition, ‘sense makers’. We can therefore position this to mean that, if learners are sense makers, then learning strategies are essentially cognitive processes used when learners are striving to make sense out of newly presented material. This paper intends to demonstrate that such thoughts and behaviours can be made explicit and that students can co-ordinate the basic cognitive processes of selecting, organising and integrating. I will discuss two learning strategies which were developed during three cycles of an action research enquiry with a group of illustration students. While each cycle had its own particular structure and aims, the main task, that of illustrating a passage of expository text into an illustration was a constant factor. The first learning strategy involved assisting students develop ‘macropropositions’—personal understandings of the gist or essence of a text (Louwerse and Graesser, 2006; Armbruster, Anderson and Ostertag, 1987; Van Dijk & Kintsch, 1983). The second learning strategy used a form of induction categorised as analogical reasoning (Holyoak, 2005; Sloman and Lagnado, 2005). Both strategies were combined to illustrate the expository text extract. The data suggests that design students benefit from a structured approach to learning, where thinking processes and approaches can be identified and accessible for other learning situations. The research methodology is based on semi-structured interviews, questionnaires, developmental design (including student notes) and final design output. All student names used are pseudonyms. The text extract from ‘Through the Magic Door’ an essay Sir Arthur Conan Doyle, (1907) has been included as it provides context to analysis outcomes, student comments and design outputs. Keywords: Action Research; Illustration; Macrostructures; Analogical Reasoning; Learning Strategies</p

Inhibitory control during selective retrieval may hinder subsequent analogical thinking

Analogical reasoning is a complex cognitive activity that involves access and retrieval of pre-existing knowledge in order to find a suitable solution. Prior work has shown that analogical transfer and reasoning can be influenced by unconscious activation of relevant information. Based on this idea, we report two experiments that examine whether reduced access to relevant information in memory may further disrupt analogical reasoning unwittingly. In both experiments, we use an adaptation of the retrieval practice paradigm [1] to modulate memory accessibility of potential solutions to a subsequent set of analogy problems of the type ‘A is to B as C is to ?’. Experiment 1 showed a retrieval-induced impairment in analogical problem solving. Experiment 2 replicated this finding and demonstrated that it cannot be due to the deliberative episodic retrieval of the solutions to the analogies. These findings, predictable from an inhibitory framework of memory control, provide a new focus for theories of analogical transfer and highlight the importance of unconscious memory processes that may modulate problem solving.The study was supported by the Spanish Ministry of Education and Science and Ministry of Economy, Industry and Competitiveness grants FPU014/07066 to TMV, PSI2015-65502-C2-1-P to TB, PSI2015-65502-C2-2-P to CJGA and PCIN- 2015-165-C02-01 to TMV, TB and CJG