We present a theoretical account of implicit and explicit learning in terms of ACT-R, an integrated architecture of human cognition as a computational supplement to Dienes & Perner's conceptual analysis of knowledge. Explicit learning is explained in ACT-R by the acquisition of new symbolic knowledge, whereas implicit learning amounts to statistically adjusting subsymbolic quantities associated with that knowledge. We discuss the common foundation of a set of models that are able to explain data gathered in several signature paradigms of implicit (...) learning. (shrink)

In this paper we identify and characterize an analysis of two problematic aspects affecting the representational level of cognitive architectures (CAs), namely: the limited size and the homogeneous typology of the encoded and processed knowledge. We argue that such aspects may constitute not only a technological problem that, in our opinion, should be addressed in order to build arti cial agents able to exhibit intelligent behaviours in general scenarios, but also an epistemological one, since they limit the plausibility of the (...) comparison of the CAs' knowledge representation and processing mechanisms with those executed by humans in their everyday activities. In the fi nal part of the paper further directions of research will be explored, trying to address current limitations and future challenges. (shrink)

Newell proposed that cognitive theories be developed in an effort to satisfy multiple criteria and to avoid theoretical myopia. He provided two overlapping lists of 13 criteria that the human cognitive architecture would have to satisfy in order to be functional. We have distilled these into 12 criteria: flexible behavior, real-time performance, adaptive behavior, vast knowledge base, dynamic behavior, knowledge integration, natural language, learning, development, evolution, and brain realization. There would be greater theoretical progress if we evaluated theories by a (...) broad set of criteria such as these and attended to the weaknesses such evaluations revealed. To illustrate how theories can be evaluated we apply these criteria to both classical connectionism and the ACT-R theory. The strengths of classical connectionism on this test derive from its intense effort in addressing empirical phenomena in such domains as language and cognitive development. Its weaknesses derive from its failure to acknowledge a symbolic level to thought. In contrast, ACT-R includes both symbolic and subsymbolic components. The strengths of the ACT-R theory derive from its tight integration of the symbolic component with the subsymbolic component. Its weaknesses largely derive from its failure, as yet, to adequately engage in intensive analyses of issues related to certain criteria on Newell's list. Key Words: cognitive architecture; connectionism; hybrid systems; language; learning; symbolic systems. (shrink)

Quantum probability (QP) theory provides an alternative account of empirical phenomena in decision making that classical probability (CP) theory cannot explain. Cognitive architectures combine probabilistic mechanisms with symbolic knowledge-based representations (e.g., heuristics) to address effects that motivate QP. They provide simple and natural explanations of these phenomena based on general cognitive processes such as memory retrieval, similarity-based partial matching, and associative learning.

We present an account of processing capacity in the ACT-R theory. At the symbolic level, the number of chunks in the current goal provides a measure of relational complexity. At the subsymbolic level, limits on spreading activation, measured by the attentional parameter W, provide a theory of processing capacity, which has been applied to performance, learning, and individual differences data.

The commentaries on our article encourage us to believe that researchers are beginning to take seriously the goal of achieving the broad adequacy that Newell aspired to. The commentators offer useful elaborations to the criteria we suggested for the Newell Test. We agree with many of the commentators that classical connectionism is too restrictive to achieve this broad adequacy, and that other connectionist approaches are not so limited and can deal with the symbolic components of thought. All these approaches, including (...) ACT-R, need to accept the idea that progress in science is a matter of better approximating these goals, and it is premature to be making judgments of true or false. (shrink)

Recent years have seen a gradual convergence of seemingly distant research fields over a single goal: understanding and replicating biological intelligence in artifacts. This work presents a general overview on the origin, the state-of-the-art, scientific challenges and the future of Biologically Inspired Cognitive Architecture (BICA) research. Our perspective decomposes the field into the four principal semantic components associated with the BICA challenge that together call for an integration of efforts of researchers across disciplines. Areas and directions of study where new (...) integrated efforts will be primarily needed are summarized. (shrink)

This paper presents a learning theory pertinent to dynamic decision making (DDM) called instancebased learning theory (IBLT). IBLT proposes five learning mechanisms in the context of a decision‐making process: instance‐based knowledge, recognition‐based retrieval, adaptive strategies, necessity‐based choice, and feedback updates. IBLT suggests in DDM people learn with the accumulation and refinement of instances, containing the decision‐making situation, action, and utility of decisions. As decision makers interact with a dynamic task, they recognize a situation according to its similarity to past instances, (...) adapt their judgment strategies from heuristic‐based to instance‐based, and refine the accumulated knowledge according to feedback on the result of their actions. The IBLT's learning mechanisms have been implemented in an ACT‐R cognitive model. Through a series of experiments, this paper shows how the IBLT's learning mechanisms closely approximate the relative trend magnitude and performance of human data. Although the cognitive model is bounded within the context of a dynamic task, the IBLT is a general theory of decision making applicable to other dynamic environments. (shrink)

The purpose of cognitive models is to make predictive simulations of human behaviour, but this is often done at the aggregate level. Cranford, Gonzalez, Aggarwal, Cooney, Tambe, and Lebiere show that they can automatically customize a model to a particular individual on‐the‐fly, and use it to make specific predictions about their next actions, in the context of a particular cybersecurity game.

We argue that cognitive models can provide a common ground between human users and deep reinforcement learning (Deep RL) algorithms for purposes of explainable artificial intelligence (AI). Casting both the human and learner as cognitive models provides common mechanisms to compare and understand their underlying decision-making processes. This common grounding allows us to identify divergences and explain the learner's behavior in human understandable terms. We present novel salience techniques that highlight the most relevant features in each model's decision-making, as well (...) as examples of this technique in common training environments such as Starcraft II and an OpenAI gridworld. (shrink)

In his famous 1982 paper, Allen Newell [22, 23] introduced the notion of knowledge level to indicate a level of analysis, and prediction, of the rational behavior of a cognitive arti cial agent. This analysis concerns the investigation about the availability of the agent knowledge, in order to pursue its own goals, and is based on the so-called Rationality Principle (an assumption according to which "an agent will use the knowledge it has of its environment to achieve its goals" [22, (...) p. 17]. By using the Newell's own words: "To treat a system at the knowledge level is to treat it as having some knowledge, some goals, and believing it will do whatever is within its power to attain its goals, in so far as its knowledge indicates" [22, p. 13]. In the last decades, the importance of the knowledge level has been historically and system- atically downsized by the research area in cognitive architectures (CAs), whose interests have been mainly focused on the analysis and the development of mechanisms and the processes governing human and (arti cial) cognition. The knowledge level in CAs, however, represents a crucial level of analysis for the development of such arti cial general systems and therefore deserves greater research attention [17]. In the following, we will discuss areas of broad agree- ment and outline the main problematic aspects that should be faced within a Common Model of Cognition [12]. Such aspects, departing from an analysis at the knowledge level, also clearly impact both lower (e.g. representational) and higher (e.g. social) levels. (shrink)

Human relations are driven by social events—people interact, exchange information, share knowledge and emotions, and gather news from mass media. These events leave traces in human memory, the strength of which depends on cognitive factors such as emotions or attention span. Each trace continuously weakens over time unless another related event activity strengthens it. Here, we introduce a novel cognition-driven social network model that accounts for cognitive aspects of social perception. The model explicitly represents each social interaction as a trace (...) in human memory with its corresponding dynamics. The strength of the trace is the only measure of the influence that the interactions had on a person. For validation, we apply our model to NetSense data on social interactions among university students. The results show that CogSNet significantly improves the quality of modeling of human interactions in social networks. (shrink)

This work is an initial step toward developing a cognitive theory of cyber deception. While widely studied, the psychology of deception has largely focused on physical cues of deception. Given that present‐day communication among humans is largely electronic, we focus on the cyber domain where physical cues are unavailable and for which there is less psychological research. To improve cyber defense, researchers have used signaling theory to extended algorithms developed for the optimal allocation of limited defense resources by using deceptive (...) signals to trick the human mind. However, the algorithms are designed to protect against adversaries that make perfectly rational decisions. In behavioral experiments using an abstract cybersecurity game (i.e., Insider Attack Game), we examined human decision‐making when paired against the defense algorithm. We developed an instance‐based learning (IBL) model of an attacker using the Adaptive Control of Thought‐Rational (ACT‐R) cognitive architecture to investigate how humans make decisions under deception in cyber‐attack scenarios. Our results show that the defense algorithm is more effective at reducing the probability of attack and protecting assets when using deceptive signaling, compared to no signaling, but is less effective than predicted against a perfectly rational adversary. Also, the IBL model replicates human attack decisions accurately. The IBL model shows how human decisions arise from experience, and how memory retrieval dynamics can give rise to cognitive biases, such as confirmation bias. The implications of these findings are discussed in the perspective of informing theories of deception and designing more effective signaling schemes that consider human bounded rationality. (shrink)

Today's digital revolution is a worldwide phenomenon, with profound and often differential implications for communities around the world and their relationships to one another. This book presents a new, explicitly international theory of media ethics, incorporating non-Western perspectives and drawing deeply on both moral philosophy and the philosophy of technology. Clifford Christians develops an ethics grounded in three principles - truth, human dignity, and non-violence - and shows how these principles can be applied across a wide range of cases and (...) domains. The book is a guide for media professionals, scholars, and educators who are concerned with the global ramifications of new technologies and with creating a more just world. (shrink)

Les disciplines historiques, littéraires et philosophiques font un emploi abondant des catégories historiographiques. Parmi celles-ci, les termes en ismes sont très fréquents pour référer à une doctrine, un courant artistique, une idéologie ou des événements spécifiques. On fait cependant remarquer que ces désignations posent de nombreux problèmes d’interprétation. En particulier, que l’origine exacte d’une catégorie est souvent méconnue et que sa signification est plus équivoque qu’on ne le croit habituellement. La formation d’un terme en isme s’explique souvent dans un contexte (...) polémique et sert à condamner ou critiquer plutôt qu’à comprendre une pensée, un mouvement ou des faits historiques. Les catégories d’athéisme, de classicisme ou de féminisme en sont de bons exemples. Le présent volume vise à contribuer à l’étude critique des catégories historiographiques et des notions en isme en s’attardant à l’époque moderne (XVI e XVIII e siècles). Il s’agit d’un moment clef de l’histoire européenne pendant laquelle nombre de ces notions apparaissent ou pour laquelle l’historiographie en a fait un emploi abondant. Les chapitres en examinent la valeur théorique par rapport à une origine ou des usages, et déterminent de quelles manières elles contribuent à l’interprétation de l’histoire, de la littérature ou de la philosophie, de la Renaissance jusqu’à la Révolution française. (shrink)

How should you decide what to do when you’re uncertain about basic normative principles? A natural suggestion is to follow some "second-order:" norm: e.g., obey the most probable norm or maximize expected choiceworthiness. But what if you’re uncertain about second-order norms too—must you then invoke some third-order norm? If so, any norm-guided response to normative uncertainty appears doomed to a vicious regress. This paper aims to rescue second-order norms from the threat of regress. I first elaborate and defend the claim (...) some philosophers have made that the regress problem forces us to accept normative externalism, the view that at least one norm is incumbent on all agents regardless of their normative beliefs. But, I then argue, we need not accept externalism about first-order norms, thus closing off any question of how agents should respond to normative uncertainty. Rather, we can head off the threat of regress by ascribing external force to a single second-order norm: the enkratic principle. (shrink)

Decision-making under normative uncertainty requires an agent to aggregate the assessments of options given by rival normative theories into a single assessment that tells her what to do in light of her uncertainty. But what if the assessments of rival theories differ not just in their content but in their structure -- e.g., some are merely ordinal while others are cardinal? This paper describes and evaluates three general approaches to this "problem of structural diversity": structural enrichment, structural depletion, and multi-stage (...) aggregation. All three approaches have notable drawbacks, but I tentatively defend multi-stage aggregation as least bad of the three. (shrink)

The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk (like Pascal's Mugging), and intolerably paradoxical in cases like the St. Petersburg and Pasadena games. In this paper I show that, under certain conditions, stochastic dominance reasoning can capture most of the plausible implications of expectational reasoning while avoiding most of its pitfalls. Specifically, given sufficient background uncertainty (...) about the choiceworthiness of one's options, many expectation-maximizing gambles that do not stochastically dominate their alternatives "in a vacuum" become stochastically dominant in virtue of that background uncertainty. But, even under these conditions, stochastic dominance will not require agents to accept options whose expectational superiority depends on sufficiently small probabilities of extreme payoffs. The sort of background uncertainty on which these results depend looks unavoidable for any agent who measures the choiceworthiness of her options in part by the total amount of value in the resulting world. At least for such agents, then, stochastic dominance offers a plausible general principle of choice under uncertainty that can explain more of the apparent rational constraints on such choices than has previously been recognized. (shrink)

The perception of meaningful patterns in random arrangements and unrelated events takes place in our everyday lives, coined apophenia, synchronicity, or the experience of meaningful coincidences. However, we do not know yet what predicts this phenomenon. To investigate this, we re-analyzed a combined data set of two daily diary studies with a total of N = 169 participants (mean age 29.95 years; 54 men). We investigated if positive or negative affect (PA, NA) predicts the number of meaningful coincidences on the (...) following day (or vice versa). By means of a cross-lagged multilevel modelling approach (Bayesian estimation) we evaluated with which of two theoretical assumptions the data are more in line. First, if meaningful coincidences are facilitated by a broader and more flexible thinking style, PA should positively predict meaningful coincidences at the following day. However, if the experience of meaningful coincidences signifies a strategy to cope with negative feeling states, NA should predict the experience of meaningful coincidences during the following day. In favour of a more flexible thinking style, we found that PA predicted the number of perceived coincidences the following day. We did not find any effect for NA, and therefore, no evidence arguing for the coping mechanism hypothesis of meaningful coincidences. (shrink)

If I am aware that p, say, that it is raining, is it the case that I must be aware that I am aware that p? Does introspective or object-awareness entail the apprehension of mental states as being of some kind or another: self-monitoring or intentional? That is, are cognitive events implicitly self-aware or is “self-awareness” just another term for metacognition? Not surprisingly, intuitions on the matter vary widely. This paper proposes a novel solution to this classical debate by reframing (...) the problem of self-knowledge in terms of the relation between phenomenal concepts and phenomenal knowledge. Concepts of consciousness such as “introspective awareness” and “reflexive self-awareness” are grounded in phenomenal experiences rather than physical events and processes. As such they yield a different kind of self-knowledge than what can be gained by applying externalist conceptual schemas to understanding the mind. I argue that Dharmakīrti’s theory of content can be seen as endorsing the efficacy of phenomenal experience as a vehicle for self-knowledge. (shrink)

What kind of animals are human beings? And how do our visions of the human shape our theories of social action and institutions? In Moral, Believing Animals>, Christian Smith advances a creative theory of human persons and culture that offers innovative, challenging answers to these and other fundamental questions in sociological, cultural, and religious theory. Smith suggests that human beings have a peculiar set of capacities and proclivities that distinguishes them significantly from other animals on this planet. Despite the (...) vast differences in humanity between cultures and across history, no matter how differently people narrate their lives and histories, there remains an underlying structure of human personhood that helps to order human culture, history, and narration. Drawing on important recent insights in moral philosophy, epistemology, and narrative studies, Smith argues that humans are animals who have an inescapable moral and spiritual dimension. They cannot avoid a fundamental moral orientation in life and this, says Smith, has profound consequences for how sociology must study human beings. (shrink)

Our aim in this survey article is to provide an accessible overview of some key results and questions in the theory of judgment aggregation. We omit proofs and technical details, focusing instead on concepts and underlying ideas.

Many different methodological approaches have been proposed to infer the presence of consciousness in non-human systems. In this paper, a version of the theory-heavy approach is defended. Theory-heavy approaches rely heavily on considerations from theories of consciousness to make inferences about non-human consciousness. Recently, the theory-heavy approach has been critiqued in the form of Birch's (Noûs, 56(1): 133-153, 2022) dilemma of demandingness and Shevlin's (Mind & Language, 36(2): 297-314, 2021) specificity problem. However, both challenges implicitly assume an inapt characterization of (...) the theory-heavy approach. I argue that an alternative characterization of the approach, what I call a credence-based theory-heavy approach, avoids these challenges. Theorists can generate interpretations of their theory, at different levels of generality, and operationalize these into theory-informed markers. These theory-informed are assigned a likelihood and are used to assess the probability that a target system is conscious. In providing this characterization, and mapping out the possible ways in which a credence-based theory-heavy approach can be fleshed out, the aim is to situate the theory-heavy approach as a more compelling approach than it is currently being perceived as. Our attention, then, needs to towards remaining challenges such as the consensus problem and the problem of calibrating the likelihoods associated with theory-informed markers. I also explore methodological pluralism and assess how the credence-based theory-heavy approach can benefit from other methodological approaches. (shrink)

Nudge is a popular public policy tool that harnesses well-known biases in human judgement to subtly guide people’s decisions, often to improve their choices or to achieve some socially desirable outcome. Thanks to recent developments in artificial intelligence (AI) methods new possibilities emerge of how and when our decisions can be nudged. On the one hand, algorithmically personalized nudges have the potential to vastly improve human daily lives. On the other hand, blindly outsourcing the development and implementation of nudges to (...) “black box” AI systems means that the ultimate reasons for why such nudges work, that is, the underlying human cognitive processes that they harness, will often be unknown. In this paper, we unpack this concern by considering a series of examples and case studies that demonstrate how AI systems can learn to harness biases in human judgment to reach a specified goal. Drawing on an analogy in a philosophical debate concerning the methodology of economics, we call for the need of an interdisciplinary oversight of AI systems that are tasked and deployed to nudge human behaviours. (shrink)

Longtermists claim that what we ought to do is mainly determined by how our actions might affect the very long-run future. A natural objection to longtermism is that these effects may be nearly impossible to predict — perhaps so close to impossible that, despite the astronomical importance of the far future, the expected value of our present actions is mainly determined by near-term considerations. This paper aims to precisify and evaluate one version of this epistemic objection to longtermism. To that (...) end, I develop two simple models for comparing ‘longtermist’ and ‘neartermist’ interventions, incorporating the idea that it is harder to make a predictable difference to the further future. These models yield mixed conclusions: if we simply aim to maximize expected value, and don’t mind premising our choices on minuscule probabilities of astronomical payoffs, the case for longtermism looks robust. But on some prima facie plausible empirical worldviews, the expectational superiority of longtermist interventions depends heavily on these ‘Pascalian’ probabilities. So the case for longtermism may depend either on plausible but non-obvious empirical claims or on a tolerance for Pascalian fanaticism. (shrink)

One of the hallmark themes of Karl Popper’s approach to the social sciences was the insistence that when social scientists are members of the society they study, then they are liable to affect that society. In particular, they are liable to affect it in such a way that the claims they make lose their validity. “The interaction between the scientist’s pronouncements and social life almost invariably creates situations in which we have not only to consider the truth of such pronouncements, (...) but also their actual influence on future developments. The social scientist may be striving to find the truth; but, at the same time, he must always be exerting a definite influence upon society. The very fact that his pronouncements do exert an influence destroys their objectivity.” (Popper 1963. (shrink)

Contrary to a widespread belief, this book establishes that ontological and epistemological reductionism stand or fall together.

This book explores Friedrich Nietzsche's understanding of modern political culture and his position in the history of modern political thought. Surveying Nietzsche's entire intellectual career from his years as a student in Bonn and Leipzig during the 1860s to his genealogical project of the 1880s, Christian Emden contributes to a historically informed discussion of Nietzsche's response to the political predicaments of modernity, and sheds new light on the intellectual and political culture in Germany as the ideals of the Enlightenment (...) gave way to the demands of the modern nation state. This is a distinguished addition to the series of Ideas in Context, and a major reassessment of a philosopher and aphorist whose stature among post-enlightenment European thinkers is now almost unrivalled. (shrink)

Spacetime as we know and love it is lost in most approaches to quantum gravity. For many of these approaches, as inchoate and incomplete as they may be, one of the main challenges is to relate what they take to be the fundamental non-spatiotemporal structure of the world back to the classical spacetime of GR. The present essay investigates how spacetime is lost and how it may be regained in one major approach to quantum gravity, loop quantum gravity.

Legal theorists have proposed several theories to justify statutes of limitations in the criminal law, but none of these normative theories is generally accepted. This chapter investigates the related descriptive question as to whether ordinary people have the intuition that legal punishment becomes less appropriate as time passes from the date of the offense and, if they do, what factors play a role in these intuitions. Five studies demonstrate that there is an intuitive statute of limitations on both legal punishment (...) and moral criticism, and that these intuitions arise, in part, from judgments about changes in psychological connectedness over time. (shrink)

Michael S. Moore defends the ideas of free will and responsibility, especially in relation to criminal law, against several challenges from neuroscience. I agree with Moore that morality and the law presuppose a commonsense understanding of humans as rational agents, who make choices and act for reasons, and that to defend moral and legal responsibility, we must show that this commonsense understanding remains viable. Unlike Moore, however, I do not think that classical compatibilism, which is based on a conditional understanding (...) of the ability to do otherwise, provides a sufficiently robust account of free will, even when it is amended as Moore suggests. I argue that free will and responsibility can be defended more robustly by observing that, at the level of agency, there can be alternative possibilities and mental causation in a stronger sense than recognized by classical compatibilism, even if physical determinism is true. Moore’s arguments could thus be strengthened by embracing this compatibilist libertarian position. At the same time, I note that, although the idea of responsibility is robustly defensible, there are independent reasons for rejecting a retributivist approach to punishment. (shrink)

The turn of the century saw a significant increase in the amount of attention being paid by philosophers to empirical issues about moral character. Dating back at least to Plato and Aristotle in the West, and Confucius in the East, philosophers have traditionally drawn on empirical data to some extent in their theorizing about character. One of the main differences in recent years has been the source of this empirical data, namely the work of social and personality psychologists on morally (...) relevant thought and action. -/- This entry briefly examines four recent empirical approaches to moral character. It will draw on the psychology literature where appropriate, but the main focus will be on the significance of that work for philosophers interested in better understanding moral character. The four areas are situationism, the CAPS model, the Big Five model, and the VIA. The remainder of this entry devotes a section to each of them. (shrink)

Christian Georg Martin offers an argumentative reconstruction of the whole work, reading it as a critical ontology, namely as the attempt to abstract from all presuppositions and to immanently unfold conceptual determinations characterizing ...

Abstract:Organizational justice is a behavioral science concept that refers to the perception of fairness of the past treatment of the employees within an organization held by the employees of that organization. These subjective perceptions of fairness have been empirically shown to be related to 1) attitudinal changes in job satisfaction, organizational commitment and managerial trust beliefs; 2) behavioral changes in task performance activities and ancillary extra-task efforts to assist group members and improve group methods; 3) numerical changes in the quantity, (...) quality and efficiency of divisional outputs; and—though this is far more tentative—4) eventual changes in the competitive advantage and financial performance of the full organization. The authors propose that these constructs can be applied to all stakeholders, rather than just to the current employees of the firm, and that objective determinations of fairness by the managers can be related to subjective perceptions of fairness by the stakeholders that will result in the sequential series of attitudinal, behavioral and numerical changes that will lead to performance improvements. In short, the authors propose a normative stakeholder theory of the firm, based upon ethical principles, that will have testable descriptive hypotheses derived from the behavioral constructs. (shrink)