Cognitive architectures as Lakatosian research programmes: two case studies

Cognitive architectures - task-general theories of the structure and function of the complete cognitive system - are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he failed to demonstrate that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

Designing for human–agent collectives: display considerations

The adoption of unmanned systems is growing at a steady rate, with the promise of improved task effectiveness and decreased costs associated with an increasing multitude of operations. The added flexibility that could potentially enable a single operator to control multiple unmanned platforms is thus viewed as a potential game-changer in terms of both cost and effectiveness. The use of advanced technologies that facilitate the control of multiple systems must lie within control frameworks that allow the delegation of authority between the human and the machine(s). Agent-based systems have been used across different domains in order to offer support to human operators, either as a form of decision support offered to the human or to directly carry out behaviours that lead to the achievement of a defined goal. This paper discusses the need for adopting a human–agent interaction paradigm in order to facilitate an effective human–agent partnership. An example of this is discussed, in which a single human operator may supervise and control multiple unmanned platforms within an emergency response scenario

A Review of Family-Based Tests for Linkage Disequilibrium between a Quantitative Trait and a Genetic Marker

Quantitative trait transmission/disequilibrium tests (quantitative TDTs) are commonly used in family-based genetic association studies of quantitative traits. Despite the availability of various quantitative TDTs, some users are not aware of the properties of these tests and the relationships between them. This review aims at outlining the broad features of the various quantitative TDT procedures carried out in the frequently used QTDT and FBAT packages. Specifically, we discuss the “Rabinowitz” and the “Monks-Kaplan” procedures, as well as the various “Abecasis” and “Allison” regression-based procedures. We focus on the models assumed in these tests and the relationships between them. Moreover, we discuss what hypotheses are tested by the various quantitative TDTs, what testing procedures are best suited to various forms of data, and whether the regression-based tests overcome population stratification problems. Finally, we comment on power considerations in the choice of the test to be used. We hope this brief review will shed light on the similarities and differences of the various quantitative TDTs

The Illogicality of Stock-Brokers: Psychological Experiments on the Effects of Prior Knowledge and Belief Biases on Logical Reasoning in Stock Trading

BACKGROUND: Explanations for the current worldwide financial crisis are primarily provided by economists and politicians. However, in the present work we focus on the psychological-cognitive factors that most likely affect the thinking of people on the economic stage and thus might also have had an effect on the progression of the crises. One of these factors might be the effect of prior beliefs on reasoning and decision-making. So far, this question has been explored only to a limited extent. METHODS: We report two experiments on logical reasoning competences of nineteen stock-brokers with long-lasting vocational experiences at the stock market. The premises of reasoning problems concerned stock trading and the experiments varied whether or not their conclusions--a proposition which is reached after considering the premises--agreed with the brokers' prior beliefs. Half of the problems had a conclusion that was highly plausible for stock-brokers while the other half had a highly implausible conclusion. RESULTS: The data show a strong belief bias. Stock-brokers were strongly biased by their prior knowledge. Lowest performance was found for inferences in which the problems caused a conflict between logical validity and the experts' belief. In these cases, the stock-brokers tended to make logically invalid inferences rather than give up their existing beliefs. CONCLUSIONS: Our findings support the thesis that cognitive factors have an effect on the decision-making on the financial market. In the present study, stock-brokers were guided more by past experience and existing beliefs than by logical thinking and rational decision-making. They had difficulties to disengage themselves from vastly anchored thinking patterns. However, we believe, that it is wrong to accuse the brokers for their "malfunctions", because such hard-wired cognitive principles are difficult to suppress even if the person is aware of them

Particulate matter Air Pollution induces hypermethylation of the p16 promoter Via a mitochondrial ROS-JNK-DNMT1 pathway

Exposure of human populations to chronically elevated levels of ambient particulate matter air pollution < 2.5 μm in diameter (PM2.5) has been associated with an increase in lung cancer incidence. Over 70% of lung cancer cell lines exhibit promoter methylation of the tumor suppressor p16, an epigenetic modification that reduces its expression. We exposed mice to concentrated ambient PM2.5 via inhalation, 8 hours daily for 3 weeks and exposed primary murine alveolar epithelial cells to daily doses of fine urban PM (5 µg/cm2). In both mice and alveolar epithelial cells, PM exposure increased ROS production, expression of the DNA methyltransferase 1 (DNMT1), and methylation of the p16 promoter. In alveolar epithelial cells, increased transcription of DNMT1 and methylation of the p16 promoter were inhibited by a mitochondrially targeted antioxidant and a JNK inhibitor. These findings provide a potential mechanism by which PM exposure increases the risk of lung cancer

Genome-scale screen for DNA methylation-based detection markers for ovarian cancer.

The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer

Uptake of health services for common mental disorders by first-generation Turkish and Moroccan migrants in the Netherlands

Abstract Background Migration and ethnic minority status have been associated with higher occurrence of common mental disorders (CMD), while mental health care utilisation by non-Western migrants has been reported to be low compared to the general population in Western host countries. Still, the evidence-base for this is poor. This study evaluates uptake of mental health services for CMD and psychological distress among first-generation non-Western migrants in Amsterdam, the Netherlands. Methods A population-based survey. First generation non-Western migrants and ethnic Dutch respondents (N = 580) participated in structured interviews in their own languages. The interview included the Composite International Diagnostic Interview (CIDI) and the Kessler psychological distress scale (K10). Uptake of services was measured by self-report. Data were analysed using weighting techniques and multivariate logistic regression. Results Of subjects with a CMD during six months preceding the interview, 50.9% reported care for mental problems in that period; 35.0% contacted specialised services. In relation to CMD, ethnic groups were equally likely to access specialised mental health services. In relation to psychological distress, however, Moroccan migrants reported less uptake of primary care services (OR = 0.37; 95% CI = 0.15 to 0.88). Conclusion About half of the ethnic Dutch, Turkish and Moroccan population in Amsterdam with CMD contact mental health services. Since the primary purpose of specialised mental health services is to treat "cases", this study provides strong indications for equal access to specialised care for these ethnic groups. The purpose of primary care services is however to treat psychological distress, so that access appears to be lower among Moroccan migrants

From reading numbers to seeing ratios: a benefit of icons for risk comprehension

Promoting a better understanding of statistical data is becoming increasingly important for improving risk comprehension and decision-making. In this regard, previous studies on Bayesian problem solving have shown that iconic representations help infer frequencies in sets and subsets. Nevertheless, the mechanisms by which icons enhance performance remain unclear. Here, we tested the hypothesis that the benefit offered by icon arrays lies in a better alignment between presented and requested relationships, which should facilitate the comprehension of the requested ratio beyond the represented quantities. To this end, we analyzed individual risk estimates based on data presented either in standard verbal presentations (percentages and natural frequency formats) or as icon arrays. Compared to the other formats, icons led to estimates that were more accurate, and importantly, promoted the use of equivalent expressions for the requested probability. Furthermore, whereas the accuracy of the estimates based on verbal formats depended on their alignment with the text, all the estimates based on icons were equally accurate. Therefore, these results support the proposal that icons enhance the comprehension of the ratio and its mapping onto the requested probability and point to relational misalignment as potential interference for text-based Bayesian reasoning. The present findings also argue against an intrinsic difficulty with understanding single-event probabilities