Within the strong branch of artificial intelligence, which is aimed at creating thinking machines with intellectual powers like those of man, the most explored research program is symbolic aI, defined as the attempt to use electronic computers to replicate the human mind, either assuming a structural and functional similarity between them, or trying to replicate the behavior produced by the human mind through computational processes that also have an intentional structure but are only instrumentally equivalent. In this paper we show (...) that strong symbolic aI, in either of its two variants, is impossible, since formal systems, that is what all computer programs ultimately are, are not sufficient to replicate in an intentional way four intellectual faculties of man that are essential to intelligent behavior: sense of the situation, common sense, procedural skills and theory abduction. (shrink)

Commonsense psychology and cognitive science both regularly assume the existence of representational states. I propose a naturalistic theory of representation sufficient to meet the pretheoretical constraints of a "folk theory of representation", constraints including the capacities for accuracy and inaccuracy, selectivity of proper objects of representation, perspective, articulation, and "efficacy" or content-determined functionality. The proposed model states that a representing device is a device which changes state when information is received over multiple information channels originating at a single source. The (...) changed state of a representing device is a representation. The unitary information source which would give rise to the information impinging on the representing device, and hence, give rise to the representation, is the content of the representation. The model meets the pretheoretic constraints, and also conforms to available neurobiological data for two invertebrate species. (shrink)

This paper addresses questions of universality related to ontological engineering, namely aims at substantiating (negative) answers to the following three basic questions: (i) Is there a ‘universal ontology’?, (ii) Is there a ‘universal formal ontology language’?, and (iii) Is there a universally applicable ‘mode of reasoning’ for formal ontologies? To support our answers in a principled way, we present a general framework for the design of formal ontologies resting on two main principles: firstly, we endorse Rudolf Carnap’s principle of logical (...) tolerance by giving central stage to the concept of logical heterogeneity, i.e. the use of a plurality of logical languages within one ontology design. Secondly, to structure and combine heterogeneous ontologies in a semantically well-founded way, we base our work on abstract model theory in the form of institutional semantics, as forcefully put forward by Joseph Goguen and Rod Burstall. In particular, we employ the structuring mechanisms of the heterogeneous algebraic specification language HetCasl for defining a general concept of heterogeneous, distributed, highly modular and structured ontologies, called hyperontologies. Moreover, we distinguish, on a structural and semantic level, several different kinds of combining and aligning heterogeneous ontologies, namely integration, connection, and refinement. We show how the notion of heterogeneous refinement can be used to provide both a general notion of sub-ontology as well as a notion of heterogeneous equivalence of ontologies, and finally sketch how different modes of reasoning over ontologies are related to these different structuring aspects. (shrink)

The richness of humanity is the diversity of its cultures, but now as never before the destructive power of modern technology and threatening ecological disasters make it necessary that we all recognize we are many peoples of one world. Complementing the diversity of our different cultures, the growth of a common, scientific knowledge inspires the hope that we may achieve and share a secondary culture of ideas. Computers, which can help represent explicitly the best ideas of modern science, can aid (...) in the diffusion of such powerful ideas to create a popular, secondary, scientific culture.We propose that a primary objective of learning environment design should be the development of thinkable models in the minds of students; further, since thinkable models represent a level of knowledge deeper than superficial terminology and specific graphical forms, such may be an objective suitable for various people in different cultures. To pursue these notions in some detail, a taxonomy of models is developed and the issue of how representations relate to human modes of perception and action is raised. The notions are explored first through the contrasting of a half-dozen approaches to the Pythagorean Theorem; then through describing polylingual word worlds and the Rosetta disk project.Common experiences produce common models —not only public models but the cognitive structures built from those shared experiences; and shared models will permit enhanced communication and understanding. If sharing experiences through play with computer based learning environments in different languages permits children to develop common models of the world, this will ultimately enhance mutual understanding between people in different places. This objective is now within reach. (shrink)

Expert reasoning combines voluminous domain‐specific knowledge with more general factual and strategic knowledge. Whereas expert system builders have recognized the need for specificity and problem‐solving researchers the need for generality, few attempts have been made to develop expert reasoning engines combining different kinds of knowledge at different levels of generality. This paper reports on the FERMI project, a computer‐implemented expert reasoner in the natural sciences that encodes factual and strategic knowledge in separate semantic hierarchies. The principled decomposition of knowledge according (...) to type and level of specificity yields both power and cross‐doman generality, as demonstrated in FERMI's ability to apply the same principles of invariance and decomposition to solve problems in fluid statics, DC‐circuits, and centroid location. Hierarchical knowledge representation and problem‐solving principles are discussed, and illustrative problem‐solving traces are presented. (shrink)

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking (...) machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models. (shrink)

The causal theory of reference is often taken to provide a solution to the problems, such as incomparability and referential discontinuity, that the meaning-change thesis raised. I show that Kuhn successfully questioned the causal theory and Putnam's idea that reference is determined via the sameness relation of essences that holds between a sample and other members of a kind in all possible worlds. Putnam's single ‘essential' properties may be necessary but not sufficient to determine membership in a kind category. Kuhn (...) argued that extension is fixed by similarity-dissimilarity relations that are liable to change in taxonomic reorganizations of science. *Received October 2009; revised January 2010. †To contact the author, please write to: Institute of Philosophy, University of Leiden, Martin de Vrieshof 4, 2300 RS Leiden, The Netherlands; e-mail: [email protected]. (shrink)

The use of figurate numbers (e. g. in the context of elementary number theory) can be considered a heuristic in the field of problem solving or proving. In this paper, we want to discuss this heuristic from the perspectives of the semiotic theory of Peirce (“diagrammatic reasoning” and “collateral knowledge”) and cognitive psychology (“schema theory” and “Gestalt psychology”). We will make use of several results taken from our research to illustrate first-year students’ problems when dealing with figurate numbers in the (...) context of proving. The considerations taken from both theoretical perspectives will help to partly explain such phenomena. It will be shown that the use of figurate numbers must not be considered to be any kind of help for learners or some way of ‘easy’ mathematics. Working in this representational system has to be learned and practiced as another kind of knowledge is necessary for working with figurate numbers. The named findings also touch upon the concept of ‘proofs that explain’. Finally, we will highlight some implications for teaching and point to a number of demands for future research. (shrink)

FramesIn 1934 the Belgian artist René Magritte painted a room with a view. On an easel in front of the window stands a painting depicting the very piece of landscape blocked from sight. Magritte named his painting La Condition Humaine (“The Human Condition”), which is quite apt, for the life of everyone is determined by windows, doors, mirrors and many other frames. Indeed, to avert anxiety, one actually cultivates social behavior born of the fear of being “outside the frame.” Because (...) of this apprehension, we organize all reality into a series of preestablished frames. (shrink)

Task unrelated thought refers to thought directed away from the current situation; for example, a day dream. Encapsulated models of cognition propose that qualitative changes in consciousness, i.e., the production of TUT, can be explained in terms of changes in the quantity of resources deployed for task completion. In contrast, distributed models of cognition emphasize the importance of holistic processes in the generation and maintenance of task focus and are consistent with the effects of higher order variables such as schemata. (...) Three experiments were conducted on healthy participants using a categorical stimulus organization to contrast distributed and encapsulated views of cognition. Experiments 1 and 2 showed that despite the increased difficulty of the alphabetical verbal fluency task fewer TUTs were produced during category fluency condition. Experiment 3 replicated the categorical suppression of TUT while encoding and recalling information in a memory task. The results of these three experiments support the predictions derived from models of cognition emphasizing the importance of stimulus organization in the generation and maintenance of task focus and have potential importance for the scientific evaluation of cognition. (shrink)

Law is known to exist only being articulated in a language and discourse, and the students’ ability to comprehend and use its meta-language is one of the main goals for English for Legal Purposes (ELP) teaching. The knowledge of terminology enables students to fit new information (linguistic, disciplinary, factual, cultural, etc.) into the framework of the legal system they are studying. The acquisition of terminology in a foreign language implies knowledge of both conceptual content and the means of its verbalization. (...) This article argues for a cognitive approach to teaching Legal English, and frame modelling as an effective method of teaching and learning legal terminology. The heterogeneous structure of legal concepts (a permanent core and dynamic periphery) suggests the possibility of framing their verbal representations. From this perspective, legal terminology is viewed as a frame structure. Depending on the instructional objective, frame modelling may be circumscribed around a specific concept or frame level. (shrink)

In this paper, I shall assess the ontological commitments of frame-based methods of knowledge representation. Frames decompose concepts into recursive attribute-value structures. The question is: are the attribute values in frames to be interpreted as universal properties or rather as tropes? I shall argue that universals realism and trope theory face similar complications as far as non-terminal values, i.e., values which refer to the determinable properties of objects, are concerned. It is suggested that these complications can be overcome if one (...) is prepared to adopt an ontology of structured complexes. Such an ontology, in turn, is indifferent as to whether attribute values are interpreted as universals or as tropes. (shrink)

In this paper, I assess the ontological commitments of frame-based methods of knowledge representation. Frames decompose concepts into recursive attribute-value structures. Attributes are the general aspects by which a category or individual is described; their values are more or less specific properties that are assigned to the referential object. The question is: are these properties to be interpreted as universals or as tropes? Some trope theorists allege that an interpretation in terms of universals is incompatible with frames for individuals in (...) which the values of quality attributes are recursively specified by further attributes. I shall argue, however, that recursive extension poses a challenge, not specifically to the universals realist, but rather to realists about determinables as opposed to determinables nominalists. Moreover, it is suggested that even determinables realists are able to cope with recursively extended frames once they relativize relations between determinables and determinates to particular objects. It is indicated how these findings might bear on adjacent debates in the metaphysics of natural language. (shrink)

Analysts studying the nexus between language and ethnic identity have characterized ethnolinguistic ideologies as the deep structure of overt language practices. By contrast, this exploratory analysis argues for the advantages of shifting from a multi-level to a single-level explanatory model, consisting of interpretive frames and data (= aspects of sociocommunicative behavior) interpreted by way of those frames. The single-level model affords, arguably, a more unified treatment of people’s everyday inferences about ethnolinguistic identity, on the one hand, and research paradigms for (...) studying language as an ethnosemiotic resource, on the other hand. Yet the “singletiered” model does not void socioideological considerations. Instead, it assumes that a continuum stretches between (1) entrenched language prejudices, (2) efforts to use language theory to question or dislodge such prejudices, and (3) the moment-by-moment hypotheses and inferences in terms of which humans make sense of their conspecifics’ linguistic behavior, along with other ethnosemiotic cues. (shrink)

In the philosophy of mind, the controversy between realists and antirealists often concerns the logical form of sentences embedded in attitude reports. Antirealists believe that such sentences refer to psychological states; realists believe that they refer to situations or states of the world. In this essay, it is shown how these two modes of semantic representation are associated with different approaches to the computational modeling of cognitive processes. I put forward a normative account of methodology in artificial intelligence that reconciles (...) realism and antirealism, and suggest that my account sheds light on the problem of representing the logical form of attitude reports. (shrink)

The possibility of interacting with remote services in natural language opens up new opportunities for sharing knowledge and for automating services. Easy-to-use, text-based interfaces might provide more democratic access to legal information, government services, and everyday knowledge as well. However, the methodology of engineering robust natural language interfaces is very diverse, and widely deployed solutions are still yet to come. The main contribution is a detailed problem analysis on the theoretical level, which reveals that a text-based interface is best understood (...) as an artificial agent that represents the interests of the remote party who is separated in time and space from the client. A possible ethical issue about the development of such an agent is also discussed. (shrink)

This paper challenges a central tenet of constructive empiricism, namely that empirical adequacy has a privileged epistemic status. I argue that perceptions of observables are theory-wrought, and theory-wrought in the same ways as the observation sentences we use to describe those perceptions, van Fraassen can draw no privileged or fundamental distinction between what we observe and interpreting those observations through theory. Since empirical adequacy depends upon accurately describing what we observe, and we have no theory-independent reason to believe that what (...) we ‘observe’ is a reflection of what is true, then empirical adequacy can inherit no special connection to what is real via what we observe. The epistemological significance of empirical adequacy is thereby reduced. (shrink)

The present paper is meant to summarise and enlighten the theoretical implications of the twin theories of text comprehension and of text compression. Compatibility and non-exclusiveness of particle-like analysis of language and wave-like analysis of intentionality are also demonstrated within the newly established quantum linguistics framework. The informative state of language is viewed as being relatively stable; once activated and subject to motion, therefore reaching a communicative state, different phenomena occur, which may be observed, analysed and visualised through CPP-TRS observational (...) devices. Relativity theory may therefore be organised in terms of quanta with continuity and no contradiction. (shrink)

Counterintuitive concepts have been identified as major aspects of religious belief, and have been used to explain the retention and transmission of such beliefs. To resolve some inconsistencies in the literature concerning counterintuitiveness, we conducted three experiments to study the effect of context on recall. Five types of items were used: intuitive, minimally counterintuitive, maximally counterintuitive, minimally counterintuitive with contradictory context, and intuitive with contradictory context. Items were presented with context or without context and participants were asked to recall them. (...) Maximally counterintuitive concepts were found to have the poorest recall in both immediate and delayed recall conditions and regardless of the presence or absence of context. No significant differences were found in the recall rates of minimally counterintuitive concepts and intuitive concepts, although delayed recall affected minimally counterintuitive concepts less than intuitive concepts, suggesting the possibility of differential "fitness." Presence of contradictory context was found to be able to change minimally counterintuitive items into the functional equivalents of intuitive items. When relevant context was present, minimally counterintuitive concepts were recalled significantly better than intuitive concepts, which is consistent with the findings of Barrett & Nyhof. For items presented as lists, intuitive items were recalled better, consistent with the findings of Norenzayan & Atran. Thus, context was the key element affecting recall and the discrepancy among prior studies was resolved. The results imply that no "item-centered" explanation of the formation and transmission of religious concepts can be adequate in itself. Instead, the nature of the surrounding context must be included in any such account. (shrink)

Several authors have hailed intuition as one of the defining features of expertise. In particular, while disagreeing on almost anything that touches on human cognition and artificial intelligence, Hubert Dreyfus and Herbert Simon agreed on this point. However, the highly influential theories of intuition they proposed differed in major ways, especially with respect to the role given to search and as to whether intuition is holistic or analytic. Both theories suffer from empirical weaknesses. In this paper, we show how, with (...) some additions, a recent theory of expert memory (the template theory) offers a coherent and wide-ranging explanation of intuition in expert behaviour. It is shown that the theory accounts for the key features of intuition: it explains the rapid onset of intuition and its perceptual nature, provides mechanisms for learning, incorporates processes showing how perception is linked to action and emotion, and how experts capture the entirety of a situation. In doing so, the new theory addresses the issues problematic for Dreyfus’s and Simon’s theories. Implications for research and practice are discussed. (shrink)

In this article I continue reading oral traditional poetry from a cognitive perspective. This time I use findings obtained empirically from my previous research on the living short improvisational poetic genre ayyu from Morocco (Gintsburg 2017, 2019a) and turn my attention to kopla zaharrak, another short oral improvisational poetic genre, which once existed in the Basque Country but is now extinct and almost forgotten. In order to better understand how this genre once functioned, I first apply to it the notions (...) of frames, or topics or themes, and scripts, or possible scenarios manifested at least partly in form of formulaic language, which are triggered by them. The analysis reveals that on the cognitive level kopla zaharrak offer a structure similar to the ayyu, where the first two lines work as a frame and the last two lines as a script. In the second part of my research, I compare examples of kopla zaharrak and ayyus and conclude that, despite obvious cultural and linguistic differences, the way both traditions make use of images of the natural world and connect them to human situations has demonstrable similarities. (shrink)

Semantic networks were developed in cognitive science and artificial intelligence studies as graphical knowledge representation and inference tools emulating human thought processes. Formal analysis of the representation and inference capabilities of the networks modeled them as subsets of standard first-order logic (FOL), restricted in the operations allowed in order to ensure the tractability that seemed to characterize human reasoning capabilities. The graphical network representations were modeled as providing a visual language for the logic. Sub-sets of FOL targeted on knowledge representation (...) came to be called description logics, and research on these logics has focused on issues of tractability of subsets with differing representation capabilities, and on the implementation of practical inference systems achieving the best possible performance. Semantic network research has kept pace with these developments, providing visual languages for knowledge entry, editing, and presenting the results of inference, that translate unambiguously to the underlying description logics. This paper discusses the design issues for such semantic network formalisms, and illustrates them through detailed examples of significant generic knowledge structures analyzed in the literature, including determinables, contrast sets, genus/differentiae, taxonomies, faceted taxonomies, cluster concepts, family resemblances, graded concepts, frames, definitions, rules, rules with exceptions, essence and state assertions, opposites and contraries, relevance, and so on. Such examples provide important test material for any visual language formalism for logic. (shrink)

The problem of concept representation is relevant for many sub-fields of cognitive research, including psychology and philosophy, as well as artificial intelligence. In particular, in recent years it has received a great deal of attention within the field of knowledge representation, due to its relevance for both knowledge engineering as well as ontology-based technologies. However, the notion of a concept itself turns out to be highly disputed and problematic. In our opinion, one of the causes of this state of affairs (...) is that the notion of a concept is, to some extent, heterogeneous, and encompasses different cognitive phenomena. This results in a strain between conflicting requirements, such as compositionality, on the one hand and the need to represent prototypical information on the other. In some ways artificial intelligence research shows traces of this situation. In this paper, we propose an analysis of this current state of affairs. Since it is our opinion that a mature methodology with which to approach knowledge representation and knowledge engineering should also take advantage of the empirical results of cognitive psychology concerning human abilities, we outline some proposals for concept representation in formal ontologies, which take into account suggestions from psychological research. Our basic assumption is that knowledge representation systems whose design takes into account evidence from experimental psychology may therefore give better results in many applications. (shrink)

We present a model of similarity‐based retrieval that attempts to capture three seemingly contradictory psychological phenomena: (a) structural commonalities are weighed more heavily than surface commonalities in similarity judgments for items in working memory; (b) in retrieval, superficial similarity is more important than structural similarity; and yet (c) purely structural (analogical) remindings e sometimes experienced. Our model, MAC/FAC, explains these phenomena in terms of a two‐stage process. The first stage uses a computationally cheap, non‐structural matcher to filter candidate long‐term memory (...) items. It uses content vectors, a redundant encoding of structured representations whose dot product estimates how well the corresponding structural representations will match. The second stage uses SME (structure‐mapping engine) to compute structural matches on the handful of items found by the first stage. We show the utility of the MAC/FAC model through a series of computational experiments: (a) We demonstrate that MAC/FAC can model patterns of access found in psychological data; (b) we argue via sensitivity analyses that these simulation results rely on the theory; and (c) we compare the performance of MAC/FAC with ARCS, an alternate model of similarity‐based retrieval, and demonstrate that MAC/FAC explains the data better than ARCS. Finally, we discuss limitations and possible extensions of the model, relationships with other recent retrieval models, and place MAC/FAC in the context of other recent work on the nature of similarity. (shrink)

Estudio de los planos de realidad en el uso de redes sociales y servicios de mensajería instantánea, la identidad del usuario y algunos mecanismos discursivos fundamentales de la comunicación en la red. Análisis de la relación paralela entre la realidad física y los escenarios virtuales, la identidad estática y el escaparatismo de las redes sociales y el papel que juegan el monólogo, el contexto y los topoi en el ciber-discurso. El estudio de las herramientas de interacción de las redes sociales (...) y de los propósitos discursivos indican el desarrollo de dinámicas de participación o proyección, un trasvase de identidad y una masificación informativa en detrimento del conocimiento. Se observa la necesidad de una macro-gestión de datos debido a la realidad plural emergente, la posibilidad de crear una identidad digital inalterable y el uso de los escenarios virtuales como lanzaderas de comunicación, más que como medios de interacción. (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.

The aims of this paper are threefold: To show that game-playing (GP), the discipline of Artificial Intelligence (AI) concerned with the development of automated game players, has a strong epistemological relevance within both AI and the vast area of cognitive sciences. In this context games can be seen as a way of securely reducing (segmenting) real-world complexity, thus creating the laboratory environment necessary for testing the diverse types and facets of intelligence produced by computer models. This paper aims to promote (...) the belief that games represent an excellent tool for the project of computational psychology (CP). To underline how, despite this, GP has mainly adopted an engineering-inspired methodology and in doing so has distorted the framework of cognitive functionalism. Many successes (i.e. chess, checkers) have been achieved refusing human-like reasoning. The AI has appeared to work well despite ignoring an intrinsic motivation, that of creating an explanatory link between machines and mind. To assert that substantial improvements in GP may be obtained in the future only by renewed interest in human-inspired models of reasoning and in other cognitive studies. In fact, if we increase the complexity of games (from NP-Completeness to AI-Completeness) in order to reproduce real-life problems, computer science techniques enter an impasse. Many of AI’s recent GP experiences can be shown to validate this. The lack of consistent philosophical foundations for cognitive AI and the minimal philosophical commitment of AI investigation are two of the major reasons that play an important role in explaining why CP has been overlooked. (shrink)