We analyze the dynamics of repeated interaction of two players in the Prisoner's Dilemma under various levels of interdependency information and propose an instance-based learning cognitive model to explain how cooperation emerges over time. Six hypotheses are tested regarding how a player accounts for an opponent's outcomes: the selfish hypothesis suggests ignoring information about the opponent and utilizing only the player's own outcomes; the extreme fairness hypothesis weighs the player's own and the opponent's outcomes equally; the moderate fairness hypothesis weighs (...) the opponent's outcomes less than the player's own outcomes to various extents; the linear increasing hypothesis increasingly weighs the opponent's outcomes at a constant rate with repeated interactions; the hyperbolic discounting hypothesis increasingly and nonlinearly weighs the opponent's outcomes over time; and the dynamic expectations hypothesis dynamically adjusts the weight a player gives to the opponent's outcomes, according to the gap between the expected and the actual outcomes in each interaction. When players lack explicit feedback about their opponent's choices and outcomes, results are consistent with the selfish hypothesis; however, when this information is made explicit, the best predictions result from the dynamic expectations hypothesis. (shrink)

Shaʻar ha-ṭohorah. Liḳuṭim mi-Sefer ḥasidim -- Śiḥot u-maʼamarim.

Ḳitsur Ḥovat ha-levavot me-Rabenu Asher mi-Lunil -- Ḳitsur Ḥovat ha-levavot mi-sefer Tsedah la-derekh -- Ḳitsur Ḥovat ha-levavot ʻAśarah hilulim -- Ḳitsur Ḥovat ha-levavot Margaliyot ṭovot.

A recent critique of hierarchical Bayesian models of delusion argues that, contrary to a key assumption of these models, belief formation in the healthy (i.e., neurotypical) mind is manifestly non-Bayesian. Here we provide a deeper examination of the empirical evidence underlying this critique. We argue that this evidence does not convincingly refute the assumption that belief formation in the neurotypical mind approximates Bayesian inference. Our argument rests on two key points. First, evidence that purports to reveal the most damning violation (...) of Bayesian updating in human belief formation is counterweighted by substantial evidence that indicates such violations are the rare exception—not a common occurrence. Second, the remaining evidence does not demonstrate convincing violations of Bayesian inference in human belief updating; primarily because this evidence derives from study designs that produce results that are not obviously inconsistent with Bayesian principles. (shrink)

Intentions are an important concept in Artificial Intelligence and Cognitive Science. We present a formal theory of intentions and beliefs based on Discourse Representation Theory that captures many of their important logical properties. Unlike possible worlds approaches, this theory does not assume that agents are perfect reasoners, and gives a realistic view of their internal architecture; unlike most representational approaches, it has an objective semantics, and does not rely on an ad hoc labeling of the internal states of agents. We (...) describe a minimal logic for intentions and beliefs that is sound and complete relative to our semantics. We discuss several additional axioms, and the constraints on the models that validate them. (shrink)

The Defective Image develops the argument that Darwinism is predicated on a profound epistemological flaw and proposes to demonstrate that the limitations in Darwinism can be illustrated by its inability to furnish a credible explanation for communication. The author argues that Darwinism is more faith-based ideology than scientific theory and that its character as a faith-based ideology accounts for much of the rancor that characterizes the current debate over evolution.

In his 2012 book Jussim argues that the self-fulfilling prophecy and expectancy effects of descriptive stereotypes are not potent shapers of social reality. However, his conclusion that descriptive stereotypesper sedo not shape social reality is premature and overly reductionist. We review evidence that suggests descriptive stereotypes do have a substantial influence on social reality, by virtue of their influence on collective action.

Boyer & Petersen argue that folk-economic beliefs are widespread – shaped by evolved cognitive systems – and they offer exemplar beliefs to illustrate their thesis. In this commentary, we highlight evidence of substantial variation in one of these exemplars: beliefs about immigration. Contra claims by B&P, we argue that the balance of this evidence suggests the “folk” may actually holdpositivebeliefs about the economic impact of immigration.

Critical Thinking in Clinical Research explains the fundamentals of clinical research in a case-based approach. The core concept is to combine a clear and concise transfer of information and knowledge with an engagement of the reader to develop a mastery of learning and critical thinking skills. The book addresses the main concepts of clinical research, basics of biostatistics, advanced topics in applied biostatistics, and practical aspects of clinical research, with emphasis on clinical relevance across all medical specialties.

Purpose Online violence has been rampant in the past decade, intensifying the victims’ suffering owing to its rapid dissemination to vast audiences. This study aims to focus on online gender-based violence directed against young Bedouin women who have left their male-dominated home territory for academic studies. This study examined how the backlash against these students, intended to stop changes in traditional gender roles, is reflected in offensive TikTok videos. Design/methodology/approach This research is based on a qualitative-thematic analysis of 77 questionnaires (...) and 30 semistructured in-depth interviews with first-year female Bedouin students aged 18–21 years. Findings The backlash was widespread, with young Bedouin men using offensive videos as “proof” that women have violated codes of honor and morality. The videos exhibited four types of gender-based violence: claims of immoral behavior, aggressive captions that take the footage out of context, allegations of immodest clothing and digital photo editing that produced fabricated results. Examining participants' reactions to the videos, this study revealed two patterns of response: passive acceptance of the situation and an active approach that included reaching out to powerful Bedouin men for solutions. Originality/value This research enriches the literature on online gender-based violence, particularly against women in traditional societies, and suggests practical steps: developing online media literacy in traditional societies, adopting a proactive approach and nurturing social self-competence in women who have been victims of online gender-based violence. (shrink)

Mechanistic models are built using knowledge as the primary information source, with well-established biological and physical laws determining the causal relationships within the model. Once the causal structure of the model is determined, parameters must be defined in order to accurately reproduce relevant data. Determining parameters and their values is particularly challenging in the case of models of pathophysiology, for which data for calibration is sparse. Multiple data sources might be required, and data may not be in a uniform or (...) desirable format. We describe a calibration strategy to address the challenges of scarcity and heterogeneity of calibration data. Our strategy focuses on parameters whose initial values cannot be easily derived from the literature, and our goal is to determine the values of these parameters via calibration with constraints set by relevant data. When combined with a covariance matrix adaptation evolution strategy, this step-by-step approach can be applied to a wide range of biological models. We describe a stepwise, integrative and iterative approach to multiscale mechanistic model calibration, and provide an example of calibrating a pathophysiological lung adenocarcinoma model. Using the approach described here we illustrate the successful calibration of a complex knowledge-based mechanistic model using only the limited heterogeneous datasets publicly available in the literature. (shrink)