Connectionist models provide a promising alternative to the traditional computational approach that has for several decades dominated cognitive science and artificial intelligence, although the nature of connectionist models and their relation to symbol processing remains controversial. Connectionist models can be characterized by three general computational features: distinct layers of interconnected units, recursive rules for updating the strengths of the connections during learning, and “simple” homogeneous computing elements. Using just these three features one can construct surprisingly elegant and powerful models of (...) memory, perception, motor control, categorization, and reasoning. What makes the connectionist approach unique is not its variety of representational possibilities or its departure from explicit rule-based models, or even its preoccupation with the brain metaphor. Rather, it is that connectionist models can be used to explore systematically the complex interaction between learning and representation, as we try to demonstrate through the analysis of several large networks. (shrink)

Cognitive Science is a promising field of research that deals with one of the most fundamental questions ever: how do beings know? However, despite the long and extensive tradition of the field it has not yet become an area of knowledge with scientific identity. This is primarily due to three reasons: the lack of boundaries in defining the object of study, i.e. cognition, the lack of a precise, robust and consistent scientific methodology and results, and the inner problems derived from (...) its interdisciplinary nature. This paper presents a background review, a theoretical frame and a humble reflection on these topics in order to arouse the internal debate among readers once more. (shrink)

The current renewal of connectionist techniques using networks of neuron-like units has started to have an influence on cognitive modelling. However, compared with classical artificial intelligence methods, the position of connectionism is still not clear. In this article artificial intelligence and connectionism are systematically compared as cognitive models so as to bring out the advantages and shortcomings of each. The problem of structured representations appears to be particularly important, suggesting likely research directions.

After the setbacks suffered in the 1970s as a result of the ‘Lighthill Report’ (Lighthill, 1973), the science of Artificial Intelligence (AI) has undergone a dramatic revival of fortunes in the 1980s. But despite the obvious enormity and complexity of the problems tackled by AI, it still remains rather parochial in relation to the import of alternative though potentially fruitful ideas from other disciplines. With this in mind, the aim of the present paper is to utilise ideas from the sociology (...) of science in order to explore some current issues in AI and, in particular, the branch of expert systems.It is argued that the sociology of sciences shares a common focus of enquiry along with AI — namely, the nature of knowledge — and has a role to play in the understanding, design and future development of expert systems. (shrink)

Jean Piaget, along with Sigmund Freud and B. F. Skinner, is one of the most influential thinkers in psychology. His influence on developmental and cognitive psychology, pedagogy and the so-called cognitive revolution is without doubt. The contributors to the book under review aim to show his past, contemporary as well as future relevance to important areas of psychology. I argue that they fail because they use Piaget’s own terminology, instead of explaining his ideas and relevance in a way accessible to (...) someone not already familiar with or sceptical about his assumptions and ideas. Thus, the book neither meets the authors’ own stated goals, nor provides an accessible exposition of Piaget for the uninitiated or sceptical reader. A companion book like this one should help give answers to questions which someone unfamiliar with or sceptical of, but curious about, Piaget’s work would ask. (shrink)

Anthropology and the other cognitive science (CS) subdisciplines currently maintain a troubled relationship. With a debate in topiCS we aim at exploring the prospects for improving this relationship, and our introduction is intended as a catalyst for this debate. In order to encourage a frank sharing of perspectives, our comments will be deliberately provocative. Several challenges for a successful rapprochement are identified, encompassing the diverging paths that CS and anthropology have taken in the past, the degree of compatibility between (1) (...) CS and (2) anthropology with regard to methodology and (3) research strategies, (4) the importance of anthropology for CS, and (5) the need for disciplinary diversity. Given this set of challenges, a reconciliation seems unlikely to follow on the heels of good intentions alone. (shrink)

. The human brain combines empathy and imagination via the old brain which sets our destiny in the evolutionary scheme of things. This new understanding of cognition is an emergent phenomenon—basically an expressive ordering of reality as part of “a single natural system.” The holographic and subsymbolic paradigms suggest that we live in a contextual universe, one which we create and yet one in which we are required to adapt. The inadequacy of the new brain—specially the left hemisphere's rational view (...) of destiny—is replaced by a view of a new relatedness in reality in which human destiny comes from and depends upon the mutual interchange between the new brain and the old brain for the survival of what is significant to the whole systemic context in which we live. (shrink)

This paper sketches an alternative answer to James Jones's recent attempt to explore the implications of cognitive social learning theories of personality for issues in epistemology, philosophy of science, and religious studies. Since the 1960s, two cognitive revolutions have taken place in scientific psychology: the first made cognition central to theories of perception, memory, problem solving, and so on; the second made cognition central to theories of learning and behavior, among others. Cognitive social learning theories find their place in the (...) latter revolution. Because of an ongoing naturalistic revolution in philosophy, these cognitive revolutions in psychology are having a profound effect on both descriptive and normative issues in epistemology and philosophy of science. From the naturalistic perspective, philosophy cannot adequately pursue its goals without the contributions of the empirical sciences, including psychology. The author concludes that the cognitive revolutions in psychology and the naturalistic revolution in philosophy have similar descriptive and normative import for the study of religion. (shrink)

As human beings we inevitably try to explain our experience. In philosophical language, we deal with transcendent assertions and aspirations. The issue, then, is: how can we talk about what matters, given the structures inherent in language and basic to the way we are made? Instead of the philosophical category of Being, I advance a case for giving the human brain privileged status as an analogical expression of God, the symbol‐concept of what matters most, and then suggest the illumination which (...) can come with using that analogical expression, especially as that analogy connects us with the environment at the limbic level and constructs our world at the cerebral level. (shrink)

This paper proposes a model ofratio decidendi as a justification structure consisting of a series of reasoning steps, some of which relate abstract predicates to other abstract predicates and some of which relate abstract predicates to specific facts. This model satisfies an important set of characteristics ofratio decidendi identified from the jurisprudential literature. In particular, the model shows how the theory under which a case is decided controls its precedential effect. By contrast, a purely exemplar-based model ofratio decidendi fails to (...) account for the dependency of precedential effect on the theory of decision. (shrink)

En este trabajo se realiza una propuesta de comunicación transdisciplinar entre las ciencias cognitivas y la educación, tal y como se perfilan en el siglo XXI. En un primer lugar se contextualizan estos procesos de comunicación en el continuum histórico que transita desde los inicios del siglo pasado, con la configuración de la psicología educativa dentro del constructo de las ciencias educativas; pasando por la constitución de las ciencias cognitivas, a mediados del siglo XX que propició la emergencia de la (...) síntesis disciplinar entre las ciencias del cerebro y de la mente, para posibilitar un encuadre arraigado en el presente, y en las propuestas de consiliencia entre neurociencia cognitiva y educación. Desde este presente histórico, se efectúa una propuesta de diálogo entre las distintas epistemes (educativas y cognitivas), en relación con el fenómeno de la educación bilingüe, y en concreto en el contexto intercultural ecuatoriano. La integración de los distintos niveles de análisis que configuran un fenómeno complejo, como lo es todo fenómeno educativo, refleja cómo los intentos transdisciplinares orientados a reconocer la complejidad ontológica de un mismo objeto de estudio, requiere del diálogo entre las distintas epistemologías y metodologías implicadas. La apertura del campo educativo a las dimensiones mentales y cerebrales en su expresión cognitiva, requiere en este s. XXI procesos de apertura recíproca respecto de la influencia que el eje cultura-educación ejerce en el modelamiento de los procesos de cognición y aprendizaje. (shrink)

Cognitive scientists have focused too narrowly on the acquisition of data and on the methods to extract patterns from those data. We argue that a successful science of the mind requires widening our focus to include the problems being solved by cognitive processes. Frameworks that characterize cognitive processes in terms of instrumental problem‐solving, such as those within the evolutionary social sciences, become necessary if we wish to discover more accurate descriptions of those processes.

Cognitive science was established as an interdisciplinary domain of research in the 1970s. Since then, the domain has flourished, despite disputes concerning its interdisciplinarity. Multiple methods exist for the assessment of interdisciplinary research. The present study proposes a methodology for quantifying interdisciplinary aspects of research in cognitive science. We propose models for text similarity analysis that provide helpful information about the relationship between publications and their specific research fields, showing potential as a robust measure of interdisciplinarity. We designed and developed (...) models utilizing the Doc2Vec method for analyzing cognitive science and related fields. Our findings reveal that cognitive science collaborates closely with most constituent disciplines. For instance, we found a balanced engagement between several constituent fields—including psychology, philosophy, linguistics, and computer science—that contribute significantly to cognitive science. On the other hand, anthropology and neuroscience have made limited contributions. In our analysis, we find that the scholarly domain of cognitive science has been exhibiting overt interdisciplinary for the past several decades. (shrink)

The aim of this article is to question the epistemic presuppositions of applying behavioural science in public policymaking. Philosophers of science who have examined the recent applications of the behavioural sciences to policy have contributed to discussions on causation, evidence, and randomised controlled trials. These have focused on epistemological and methodological questions about the reliability of scientific evidence and the conditions under which we can predict that a policy informed by behavioural research will achieve the policymakers’ goals. This paper argues (...) that the philosophical work of Helen Longino can also help us to have a better and fuller understanding of the knowledge which the behavioural sciences provide. The paper advances an analysis of the knowledge claims that are made in the context of policy applications of behavioural science and compares them with the behavioural research on which they are based. This allows us to show that behavioural policy and the debates accompanying it are based on an oversimplified understanding of what knowledge behavioural science actually provides. Recognising this problem is important as arguments that justify reliance on the behavioural sciences in policy typically presume this simplification. (shrink)

The term ‘information’ is used extensively in biology, cognitive science and the philosophy of consciousness in relation to the concepts of ‘meaning’ and ‘causation’. While ‘information’ is a term that serves a useful purpose in specific disciplines, there is much to the concept that is problematic. Part 1 is a critique of the stance that information is an independently existing entity. On this view, and in biological contexts, systems transmit, acquire, assimilate, decode and manipulate it, and in so doing, generate (...) meaning. I provide a detailed proposal in Part 2 that supports the claim that it is the dynamic form of a system that qualifies the informational nature of meaningful interactive engagement, that is, that information is dependent on dynamic form rather than that it exists independently. In Part 3, I reflect on the importance of the distinction between the independent and dependent stances by looking specifically at the implications for how we might better interpret causation and emergence. (shrink)

Núñez et al. (2019) argue that cognitive science has failed either “to transition to a mature inter‐disciplinary coherent field” (p. 782) or “to generate a successful [Lakatosian] research program” (p. 789). We argue that the former was never the intention of many early researchers within the field, while the latter is an inappropriate criterion by which to judge an entire discipline. However, we concur with Núñez et al. (2019) that the individual disciplinary balance within cognitive science has changed over time. (...) Of particular concern is the fact that the use of computational methods appears to be on the wane. (shrink)

(2014). Emergence, Story, and the Challenge of Positive Scenarios. World Futures: Vol. 70, Strategy, Story, and Emergence: Essays on Scenario Planning, pp. 52-87.

Today, the frequency and the rate of success resulting from advances in medicine have made organ transplantations an everyday occurrence. Still, organ transplantations and donations modify the subjective experience of human beings as regards the image they have of themselves, of body, of life and of death. If the concern of the quality of life and the survival of the patients is a completely human phenomenon, the fact remains that the possibility of organ transplantation and its justification depend a great (...) deal on the culture in which we live. The exploration of the philosophical tradition allows for a reconsideration of organ transplantation. If we listen to people who have experienced the decline of one of their organs and their own rebirth through the organ of someone else, we arrive at the conclusion that they went through an extreme experience in which nothing appeared as before. All those experiences intensify philosophical questionings on the meaning of life with respect to self fulfilment. The concept of nature as the experience of others can be an authentic source from which to nourish our thoughts about organ transplantation. However, and this is our hypothesis, we need something more if we are to decide something about our own life. We need a hermeneutical stance in relation to ourselves and to our world. Philosophical counselling, as a long established tradition originating with Pythagoras and later reframed by the German philosopher Achenbach could be useful in inspiring a reflection on the good life, chiefly as it takes the form of a Socratic dialogue. (shrink)

The demise of Cartesianism as an animating force in conceptualizing mind and body relations has opened up the field to a wider variety of perspectives, like the "embodiment" of phenomenological thinkers. However, because of Cartesianism's deeply rooted psychic legacy it still makes its presence felt in various places in everyday life. This paper will explore two facets of everyday life, sports and contemplation, which lend themselves to a mind‐body cognitive dissonance affected by latent Cartesian thinking. As an alternative, we will (...) propose a more phenomenologically oriented interpretation based on what has been revealed by historical precedents as well as our empirical investigations. Keywords: Flow, Contemplation, Phenomenofogy, Sports. (shrink)

The interpretive processes required to understand the context and goals of an algorithmic task are illustrated in the use of an intelligent instructional system developed to train soldiers to monitor a computerized missile's system automatic identification of aircraft. The problems students had in understanding the identification task were addressed in INCOFT, a simulation-based intelligent instructional system that depends, in part, on human instructors to convey the task framework. Supported by recent advances in the cognitive science of instruction, the concept ofapprenticeship (...) provides a model for the student-machine as well as the student-instructor interactions observed in the use of INCOFT. The system's instantiation of apprenticeship illustrates an alternative to conventional tutorial-based design of intelligent instructional systems. (shrink)

The introductory essay to this collection correctly observes that there are many “challenges for rapprochement” between anthropology and (the rest of) cognitive science. Still, the possibilities of fruitful interchanges provide some hope for the parties getting back together, at least on an intermittent basis. This response offers some views concerning the “incompatibility” of psychology and anthropology, reviews why cognitive anthropology drifted away from cognitive science, and notes two areas of contemporary interest within cognitive anthropology that may lead to a re-engagement.

Contrary to common views that philosophy is extraneous to cognitive science, this paper argues that philosophy has a crucial role to play in cognitive science with respect to generality and normativity. General questions include the nature of theories and explanations, the role of computer simulation in cognitive theorizing, and the relations among the different fields of cognitive science. Normative questions include whether human thinking should be Bayesian, whether decision making should maximize expected utility, and how norms should be established. These (...) kinds of general and normative questions make philosophical reflection an important part of progress in cognitive science. Philosophy operates best, however, not with a priori reasoning or conceptual analysis, but rather with empirically informed reflection on a wide range of findings in cognitive science. (shrink)

As artificial intelligence (AI) becomes progressively more engaged with society, its shift from technical tool to participating in society raises questions about AI personhood. Drawing upon developmental psychology and systems theory, a mediating structure for AI proto-personhood is defined analogous to an early stage of human development. The proposed AI bridges technical, psychological, and theological perspectives on near-future AI and is structured by its hardware, software, computational, and sociotechnical systems through which it experiences its world as embodied (even for putatively (...) disembodied AI). Further social and moral construction can occur building upon a simple “self” for AI synthesized from symbolic and statistical approaches to AI. (shrink)

Metalogic is an open-ended cognitive, formal methodology pertaining to semantics and information processing. The language that mathematizes metalogic is known as metalanguage and deals with metafunctions purely by extension on patterns. A metalogical process involves an effective enrichment in knowledge as logical statements, and, since human cognition is an inherently logic–based representation of knowledge, a metalogical process will always be aimed at developing the scope of cognition by exploring possible cognitive implications reflected on successive levels of abstraction. Indeed, it is (...) basically impracticable to maintain logic–and–metalogic without paying heed to cognitive theorizing. For it is cognitively irrelevant whether possible conclusions are deduced from some premises before the premises are determined to be true or whether the premises themselves are determined to be true first and, then, the conclusions are deduced from them. In this paper we consider the term metalogic as inherently embodied under the framework referred to as cognitive science and mathematics. We propose a metalogical interpretation of Arrow’s impossibility theorem and, to that end, choice theory is understood as a mental course of action dealing with logic and metalogic issues, in which a possible mathematical approach to model a mental course of action is adopted as a systematic operating method. Nevertheless, if we look closely at the core of Arrow’s impossibility theorem in terms of metalogic, a second fundamental contribution to this framework is represented by the Nash equilibrium. As a result of the foregoing, therefore, we prove the metalogical equivalence between Arrow’s impossibility theorem and the existence of the Nash equilibrium. More specifically, Arrow’s requirements correspond to the Nash equilibrium for finite mixed strategies with no symmetry conditions. To demonstrate this proof, we first verify that Arrow’s set and Nash’s set are isomorphic to each other, both sets being under stated conditions of non–symmetry. Then, the proof is completed by virtue of category theory. Indeed, the two sets are categories that correspond biuniquely to one another and, thus, it is possible to define a covariant functor that preserves their mutual structures. According to this, we show the proof–dedicated metalanguage as a precursor to a special equivalence theorem. (shrink)

This article outlines the emergence of ABA (Applied Behaviour Analysis) in the mid-20th century, and the current popularity of ABA in the anglophone world. I draw on the work of earlier historians to highlight the role of Ole Ivar Lovaas, the most influential practitioner of ABA. I argue that reception of his initial work was mainly positive, despite concerns regarding its efficacy and use of physical aversives. Lovaas’ work, however, was only cautiously accepted by medical practitioners until he published results (...) in 1987. Many accepted the results as validation of Lovaas’ research, though both his methods and broader understanding of autism had shifted considerably since his early work in the 1960s. The article analyses the controversies surrounding ABA since the early 1990s, considering in particular criticisms made by autistic people in the ‘neurodiversity movement’. As with earlier critics, some condemn the use of painful aversives, exemplified in the campaign against the use of shock therapy at the Judge Rotenberg Center. Unlike earlier, non-autistic critics, however, many in this movement reject the ideological goals of ABA, considering autism a harmless neurological difference rather than a pathology. They argue that eliminating benign autistic behaviour through ABA is impermissible, owing to the individual psychological harm and the wider societal impact. Finally, I compare the claims made by the neurodiversity movement with those made by similar 20th- and 21st-century social movements. (shrink)

The ArgumentScientific tools—measurement and calculation instruments, techniques of inference—straddle the line between the context of discovery and the context of justification. In discovery, new scientific tools suggest new theoretical metaphors and concepts; and in justification, these tool-derived theoretical metaphors and concepts are morelikely to be accepted by the scientific community if the tools are already entrenched in scientific practice.Techniques of statistical inference and hypothesis testing entered American psychology first as tools in the 1940s and 1950s and then as cognitive theories (...) in the 1960s and 1970s. Not only did psychologists resists statistical metaphors of mind prior to the institutionalization of inference techniques in their own practice; the cognitive theories they ultimately developed about “the mind as intuitive statistician” still bear the telltale marks of the practical laboratory context in which the tool was used. (shrink)

The Computational Metaphor is an extremely influential notion, and more than any other trend has given rise to the field of Cognitive Science. Environmentalism is at present better formalised as a political movement than as a scientific paradigm, despite significant research by Gibson and his followers. This article attempts to address the difficult problem of synthesising these two apparently antagonistic research paradigms.

Exploration and reflection on the interfacing of religion and the neurosciences in the last twenty‐five years provide a unique point of convergence on the relationship between science and religion. A focus on two streams of consciousness characterized the first phase in the 1970s. Scholarship suggested correlates between the styles of analytical steps and synthetic leaps of imagination and the belief patterns of proclamation and manifestation. The use of lateralized consciousness was critiqued as covering too much as well as not attending (...) to evolutionary developments and philosophical and theological foundations. A shift to whole brain functioning with more differentiated investigations came during the second phase in the 1980s. Empirical studies corroborated the earlier analytical speculations in neurotheology and advanced the heuristic value or using the whole brain as a metaphor for understanding religion. By the third phase of the 1990s, meaning‐making and integrating consciousness emerged as shaping the agenda between religion and cognitive neuroscience. The emerging methodology combines analogical continuities among levels of complexity and metaphorical leaps of inferential patterning. (shrink)