Habilitation thesis in psychology. The book consists of a collection of reasoning studies. The experimental investigations will take us from people’s reasoning about probabilities, entailments, pragmatic factors, argumentation, and causality to morality. An overarching theme of the book is norm pluralism and individual differences in rationality research.

Due to his significant role in the development of computer technology and the discipline of artificial intelligence, Alan Turing has supposedly subscribed to the theory of mind that has been greatly inspired by the power of the said technology which has eventually become the dominant framework for current researches in artificial intelligence and cognitive science, namely, computationalism or the computational theory of mind. In this essay, I challenge this supposition. In particular, I will try to show that there is no (...) evidence in Turing’s two seminal works that supports such a supposition. His 1936 paper is all about the notion of computation or computability as it applies to mathematical functions and not to the nature or workings of intelligence. On the other hand, while his 1950 work is about intelligence, it is, however, particularly concerned with the problem of whether intelligence can be attributed to computing machines and not of whether computationality can be attributed to human intelligence or to intelligence in general. (shrink)

Book Description (Blurb): Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. -/- Beginning with an overview of the historical, methodological and technical issues in the field of Cognitively-Inspired Artificial Intelligence, (...) Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realise biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biologically and cognitive accuracy of artificial systems in order project and predict their explanatory power with respect to the natural systems taken as source of inspiration. -/- Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science. (shrink)

People cannot contemplate a proposition without believing that proposition. A model of belief fixation is sketched and used to explain hitherto disparate, recalcitrant, and somewhat mysterious psychological phenomena and philosophical paradoxes. Toward this end I also contend that our intuitive understanding of the workings of introspection is mistaken. In particular, I argue that propositional attitudes are beyond the grasp of our introspective capacities. We learn about our beliefs from observing our behavior, not from introspecting our stock beliefs. -/- The model (...) of belief fixation offered in the dissertation poses a novel dilemma for theories of rationality. One might have thought that the ability to contemplate ideas while withholding assent is a necessary condition on rationality. In short, it seems that rational creatures shouldn‘t just form their beliefs based on whatever they happen to think. However, it seems that we are creatures that automatically and reflexively form our beliefs based on whatever propositions we happen to consider. Thus, either the rational requirement that states that we must have evidence for our beliefs must be jettisoned or we must accept the conclusion that we are necessarily irrational. (shrink)

There is much discussion about whether the human mind is a computer, whether the human brain could be emulated on a computer, and whether at all physical entities are computers (pancomputationalism). These discussions, and others, require criteria for what is digital. I propose that a state is digital if and only if it is a token of a type that serves a particular function - typically a representational function for the system. This proposal is made on a syntactic level, assuming (...) three levels of description (physical, syntactic, semantic). It suggests that being digital is a matter of discovery or rather a matter of how we wish to describe the world, if a functional description can be assumed. Given the criterion provided and the necessary empirical research, we should be in a position to decide on a given system (e.g. the human brain) whether it is a digital system and can thus be reproduced in a different digital system (since digital systems allow multiple realization). (shrink)

Inquiry, Volume 57, Issue 1, Page 55-96, February 2014.

Several theories claim that dreaming is a random by-product of REM sleep physiology and that it does not serve any natural function. Phenomenal dream content, however, is not as disorganized as such views imply. The form and content of dreams is not random but organized and selective: during dreaming, the brain constructs a complex model of the world in which certain types of elements, when compared to waking life, are underrepresented whereas others are over represented. Furthermore, dream content is consistently (...) and powerfully modulated by certain types of waking experiences. On the basis of this evidence, I put forward the hypothesis that the biological function of dreaming is to simulate threatening events, and to rehearse threat perception and threat avoidance. To evaluate this hypothesis, we need to consider the original evolutionary context of dreaming and the possible traces it has left in the dream content of the present human population. In the ancestral environment human life was short and full of threats. Any behavioral advantage in dealing with highly dangerous events would have increased the probability of reproductive success. A dream-production mechanism that tends to select threatening waking events and simulate them over and over again in various combinations would have been valuable for the development and maintenance of threat-avoidance skills. Empirical evidence from normative dream content, children's dreams, recurrent dreams, nightmares, post traumatic dreams, and the dreams of hunter-gatherers indicates that our dream-production mechanisms are in fact specialized in the simulation of threatening events, and thus provides support to the threat simulation hypothesis of the function of dreaming. Key Words: dream content; dream function; evolution of consciousness; evolutionary psychology; fear; implicit learning; nightmares; rehearsal; REM; sleep; threat perception. (shrink)

This paper deals with the question: how is computation best individuated? -/- 1. The semantic view of computation: computation is best individuated by its semantic properties. 2. The causal view of computation: computation is best individuated by its causal properties. 3. The functional view of computation: computation is best individuated by its functional properties. -/- Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for that is usually that computation is individuated (...) semantically. I criticize the reasons in support of this view and its presupposition of representation and semantics. Furthermore, I argue that the only justified appeal to a representational individuation of computation might be that it is partly individuated by implicit intrinsic representations. (shrink)

In this paper I critically examine the Generality Problem and argue that it does not succeed as an objection to reliabilism. Although those who urge the Generality Problem are correct in claiming that any process token can be given indefinitely many descriptions that pick out indefinitely many process types, they are mistaken in thinking that reliabilists have no principled way to distinguish between relevant and irrelevant process types.

When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches _vehicle_ and _process_ theories of consciousness, respectively. However, while there may be space (...) for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because of the influence exerted, on the one hand, by a large body of research which purports to show that the explicit representation of information in the brain and conscious experience are _dissociable_, and on the other, by the _classical_ computational theory of mind – the theory that takes human cognition to be a species of symbol manipulation. But two recent developments in cognitive science combine to suggest that a reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer reasonable to assume that the dissociability of conscious experience and explicit representation has been adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in cognitive science as it once was. It now has a lively competitor in the form of _connectionism; _and connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It takes the form of the following simple empirical hypothesis: _phenomenal experience consists in the explicit_ _representation of information in neurally realized PDP networks_.. (shrink)

John Searle and Roger Penrose are two staunch critics of computationalism who nonetheIess believe that with the right framework the mind can be naturalized. while they may be successful in showing the shortcomings of computationalism, I argue that their alternative noncomputational frameworks equally fail to carry out the project to naturalize the mind. The main reason is their failure to resolve some fundamental incompatibilities between mind and science. Searle tries to resolve the incompatibility between the subjectivity of consciousness and the (...) objectivity of silence by means of conceptual clarification. He, howeve4 fails to deal with the concepts crucial to this incompatibility, namely, the publicness of scientific knowledge and the privacy of psychological knowledge. Penrose tries to resolve the incompatibility between the non-computationality of psychological process and the computationality of scientific process by expanding the scope of science through some radical changes in quantum physics. His strategy, howeve4 has the danger of trivializing the distinction between science and non-science thereby putting into question the very value of the project to naturalize the mind. In addition, the feasibility of this strategy remains dubious in light of the mysteries that still surround quantum physics. (shrink)

Recent evidence suggests that performance on reasoning tasks may reflect the operation of a number of distinct cognitive mechanisms and processes. This paper explores the implications of this view of the mind for the descriptive and normative assessment of reasoning. I suggest that descriptive questions such as “Are we equipped to reason using rule X?” and normative questions such as “Are we rational?” are obsolete—they do not possess a fine enough grain of architectural resolution to accurately characterize the mind. I (...) explore how this general lesson can apply to specific experimental interpretations, and suggest that 'rationality' must be evaluated along a number of importantly distinct dimensions. (shrink)

When it comes to applying computational theory to the problem of phenomenal consciousness, cognitive scientists appear to face a dilemma. The only strategy that seems to be available is one that explains consciousness in terms of special kinds of computational processes. But such theories, while they dominate the field, have counter-intuitive consequences; in particular, they force one to accept that phenomenal experience is composed of information processing effects. For cognitive scientists, therefore, it seems to come down to a choice between (...) a counter-intuitive theory or no theory at all. We offer a way out of this dilemma. We argue that the computational theory of mind doesn't force cognitive scientists to explain consciousness in terms of computational processes, as there is an alternative strategy available: one that focuses on the representational vehicles that encode information in the brain. This alternative approach to consciousness allows us to do justice to the standard intuitions about phenomenal experience, yet remain within the confines of cognitive science. (shrink)

This paper deals with the question: What are the criteria that an adequate theory of computation has to meet? 1. Smith's answer: it has to meet the empirical criterion (i.e. doing justice to computational practice), the conceptual criterion (i.e. explaining all the underlying concepts) and the cognitive criterion (i.e. providing solid grounds for computationalism). 2. Piccinini's answer: it has to meet the objectivity criterion (i.e. identifying computation as a matter of fact), the explanation criterion (i.e. explaining the computer's behaviour), the (...) right things compute criterion, the miscomputation criterion (i.e. accounting for malfunctions), the taxonomy criterion (i.e. distinguishing between different classes of computers) and the empirical criterion. 3. Von Neumann's answer: it has to meet the precision and reliability of computers criterion, the single error criterion (i.e. addressing the impacts of errors) and the distinction between analogue and digital computers criterion. 4. “Everything” computes answer: it has to meet the implementation theory criterion by properly explaining the notion of implementation. -/- According to computationalists, minds are computational. Before we can judge the plausibility of any particular computationalist theory, we need to understand what notion of computation this theory employs. Although there are extant accounts of computation, any of which may, in principle, serve as a basis for computationalism, it isn’t clear that they’re all equivalent or even adequate as accounts of computation proper. By examining plausible alternatives to Smith’s adequacy criteria, our goal here is to resist his claim that no adequate account of computation proper is possible. (shrink)

Not long ago the standard view in cognitive science was that representations are symbols in an internal representational system or language of thought and that psychological processes are computations defined over such representations. This orthodoxy has been challenged by adherents of functional analysis and by connectionists. Functional analysis as practiced by Marr is consistent with an analysis of representation that grants primacy to a stands for conception of representation. Connectionism is also compatible with this notion of representation; when conjoined with (...) functional analysis, it provides a means of analyzing psychological systems in term of rules and representations without becoming committed to symbolism. Direct theorists, who rejected the orthodox symbolist conception of representation because it violated their strictures against cognitive mediational mechanisms, should find it possible to accept rules-and-representations and information-processing analyses of the mechanisms of information pickup couched in terms of functional analysis. (shrink)

The Spinozan theory of belief fixation holds that mentally representing truth-apt propositions leads to immediately believing them. In this paper, I explore how the theory fares as a defence of doxasticism about delusions (the view that they are beliefs). Doxasticism has been criticised on the grounds that delusions typically do not abide by rational standards that we expect beliefs to conform to. If belief fixation is Spinozan, I argue, these deviations from rationality are not just compatible with, but supportive of, (...) their status as beliefs. (shrink)

Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for explaining cognition; (5) The extreme (...) dynamicist answer: computation is not required for explaining cognition. The first four answers are only accurate to a first approximation. But the “devil” is in the details. The last answer cashes in on the parenthetical “if any” in the question above. The classicist argues that cognition is symbolic computation. But digital computationalism need not be equated with classicism. Indeed, computationalism can, in principle, range from digital (and analogue) computationalism through (the weaker thesis of) generic computationalism to (the even weaker thesis of) digital (or analogue) pancomputationalism. Connectionism, which has traditionally been criticised by classicists for being non-computational, can be plausibly construed as being either analogue or digital computationalism (depending on the type of connectionist networks used). Computational neuroscience invokes the notion of neural computation that may (possibly) be interpreted as a sui generis type of computation. The extreme dynamicist argues that the time has come for a post-computational cognitive science. This paper is an attempt to shed some light on this debate by examining various conceptions and misconceptions of (particularly digital) computation. (shrink)

Interface theory is the hypothesis that inferential, representational theories of perception entail that fitness, not truth, dictates the evolution of perceptual systems. They show, with simulations, that “veridical” perceptual mappings (ones that preserve at least some of the structure of the world) are routinely out-competed by “non-veridical” interfaces (ones that make no attempt to preserve that structure). They therefore take particular aim at the direct perception, ecological approach to perception and work to show that such a system, even if technically (...) an option, would never be selected for by evolution. This paper defends the ecological approach from this novel, existential attack by showing that the ecological hypothesis is so different in kind to the inferential, representational view of perception that it simply falls outside the scope of interface theory’s critiques; ecological psychology remains a viable scientific endeavor. This analysis will show that, far from being a radical new approach to perception, interface theory is simply a clear and elegant formalization of mainstream representational psychology, and any implications interface theory may have belong solely to that branch of science. (shrink)

Frances Egan argues that the states of computational theories of vision are individuated individualistically and, as far as the theory is concerned, are not intentional. Her argument depends on equating the goals and explanatory strategies of computational psychology with those of its algorithmic level. However, closer inspection of computational psychology reveals that the computational level plays an essential role in explaining visual processes and that explanations at this level are nonindividualistic and intentional. In conclusion, I sketch an account of content (...) in which content does the sort of explanatory work that Egan denies is possible. (shrink)

According to enactivism all living systems, from single cell organisms to human beings, are ontologically endowed with some form of teleological and sense-making agency. Furthermore, enactivists maintain that: there is no fixed pregiven world and as a consequence all organisms “bring forth” their own unique “worlds” through processes of sense-making. The first half of the paper takes these two ontological claims as its central focus and aims to clarify and make explicit the arguments and motivations underlying them. Our analysis here (...) highlights three distinct but connected problems for enactivism: these arguments do not and cannot guarantee that there is no pregiven world, instead, they end up generating a contradiction whereby a pregiven world seems to in fact be tacitly presupposed by virtue of a reliance on a tacit epistemic perspectivalism which is also inherently representationalist and as a consequence makes it difficult to satisfactorily account for the ontological plurality of worlds. Taking these considerations on board, the second half of the paper then aims to develop a more robust ontologically grounded enactivism. Drawing from biosemiotic enactivism, science and technology studies and anthropology, the paper aims to present an account which both rejects a pregiven world and coherently accounts for how organisms bring forth ontologically multiple worlds. (shrink)

systematicity is. Until systematicity is adequately systematicity. Most contributors to these debates have clarified, we cannot know whether classical paid little or no attention to the alleged empirical.

This thesis is set out as a collection of self-standing essays. Throughout these essays, I try to illuminate a number of controversies surrounding the way in which delusions are formed, and relatedly, their nature and epistemic standing. In Chapter 2, after an introductory chapter, I flesh out a new ‘endorsement’ approach to the Capgras delusion, the main idea being that the delusion is formed by endorsing the content of a metaphorical-perceptual state in which a loved one is represented metaphorically as (...) an imposter. In Chapter 3, I take issue with the idea, prevalent in the literature, that Bayesian accounts of inference in delusions are best characterised as versions of ‘explanationism’. Taking one such influential account as a test case, I argue that it is no more or less compatible with the endorsement alternative, which says delusions are acquired non-inferentially from experience. In Chapter 4, I examine a recent critique of predictive processing theories of delusions, according to which such theories suffer two limitations: they fail to explain why an agent believes something delusional as opposed to nothing at all or something else; they fail to explain how delusional hypotheses are generated in the first place. I suggest ways in which these concerns might be addressed. In Chapter 5, I consider how the Spinozan theory of belief fixation can improve the prospects of doxasticism about delusions. Doxasticism has been criticised on the grounds that delusions typically do not abide by rational standards which we expect beliefs to conform to. If belief fixation is Spinozan, I argue, these deviations from rationality are not just compatible with, but supportive of, their status as beliefs. In Chapter 6, I ask whether misidentification delusions formed via endorsement processes have any measure of perceptual justification. To give the best chance of getting a ‘yes’ answer, I address the question from the perspective of perceptual dogmatism, as this appears the best option if we are to grant at least defeasible justifiedness to MDs. I argue that, even so, MDs are completely unjustified. (shrink)

Since the publication of Fodor's (1983) The Modularity of Mind, there have been quite a few discussions of cognitive modularity among cognitive scientists. Generally, in those discussions, modularity means a property of specialized cognitive processes or a domain-specific body of information. In actuality, scholars understand modularity in many different ways. Different characterizations of modularity and modules were proposed and discussed, but they created misunderstanding and confusion. In this article, I classified and analyzed different approaches to modularity and argued for the (...) unity of modularity. Modularity is a multidimensional property consisting of features from several dimensions specifying different aspects of cognition. Among those, there are core features of modularity, and these core features form a cross-dimensional unity. Despite the diverse and liberal characterizations, modularity contributes to cognitive science because of the unity of the core features. (shrink)

Many philosophers and psychologists who approach the issue of representation from a computational or measurement theoretical perspective end up having to deny the possibility of junk representations—representations present in an organism's head but that enter into no psychological processes or produce no behaviour. However, I argue, a more functional perspective makes the possibility of junk representations intuitively quite plausible—so much so that we may wish to question those views of representation that preclude the possibility of junk representations. I explore some (...) of the reasons we should care about the possibility of junk representations and conclude with some speculation about whether junk representations are in fact present in our heads. (shrink)

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)

The dynamical hypothesis claims that cognitive systems, such as teams, are dynamical systems (i.e., an interdependent collection of individuals and their technology that change together over time). Following this hypothesis, team researchers have adopted dynamical approaches to better understand the team cognitive processes and states that form team cognition, as well as how they emerge over time. One approach focuses on team coordination dynamics, which examines the coupling of signals between interacting individuals in various modalities, and has been shown to (...) reflect aspects of team functioning including team cognition. However, how changes in team coordination relate to high-level team cognitive processes and states, as well as important events, are not yet fully understood. To this end, we advance a methodological framework for researching team cognition under the dynamical hypothesis. Subsequently, we provided an empirical case-study application of this framework. Thereby, this work contributes methodologically and empirically to a deeper understanding of team cognition, the dynamical hypothesis, and the synergy between them. (shrink)

Man’s intellectual capacity remains an enigma, as it is both the subject and the means of analysis. If one is to assume quantum-wave dualism in physics then the state of the world depends on the instruments we use for observation. The “paradoxical” nature of investigating human cognition may thus bear inherent limitations. However, studying cognitive models may be less of a seemingly inconsistent endeavor, if “contradictions” may be classified. In this brief exposition, a variety of aspects related to cognitive models (...) are discussed. The authors maintain that modeling the functional “paradoxical nature” of human cognition remains the greatest challenge. Therefore, consciousness aside, models of conscious systems, or rather conscious models of conscious systems, are the main objects of exploration. While intentional systems may seem a good starting point for such an exploration, they lack two important constructs: volition and reflexion. Both concepts, and especially volition, unlike rationality for example, are less discussed in the discourse of cognitive models. Although not devoted to volition or reflexion, this work proposes an increased research interest in these areas. (shrink)

In the twentieth century, no person epitomized more dramatically the “Renaissance mind” than Herbert A. Simon (1916–2001). In aworking life spanning over 60 years, Simon made seminal contributions to administrative theory, axiomatic foundations of physics, economics, sociology, econometrics, cognitive psychology, logic of scientific discovery, and artificial intelligence. Simon's life of the mind, thus, affords nothing less than a “laboratory” in which to observe and examine at close quarters the phenomenon ofmultidisciplinary creativity. In this paper, we attempt to shed some light (...) on the nature of Simon's creativity and the nature of his particular Renaissance mind. In particular, we have attempted here to articulate thecognitive styleunderlying Simon's multidisciplinary creativity. (shrink)