A cognitive architecture aimed at cumulative learning must provide the necessary information and control structures to allow agents to learn incrementally and autonomously from their experience. This involves managing an agent's goals as well as continuously relating sensory information to these in its perception-cognition information processing stack. The more varied the environment of a learning agent is, the more general and flexible must be these mechanisms to handle a wider variety of relevant patterns, tasks, and goal structures. While many researchers (...) agree that information at different levels of abstraction likely differs in its makeup and structure and processing mechanisms, agreement on the particulars of such differences is not generally shared in the research community. A dual processing architecture has been proposed as a model of cognitive processing, and they are often considered as responsible for low- and high-level information, respectively. We posit that cognition is not binary in this way and that knowledge at any level of abstraction involves what we refer to as neurosymbolic information, meaning that data at both high and low levels must contain both symbolic and subsymbolic information. Further, we argue that the main differentiating factor between the processing of high and low levels of data abstraction can be largely attributed to the nature of the involved attention mechanisms. We describe the key arguments behind this view and review relevant evidence from the literature. (shrink)

Anxious major depressive disorder is a common subtype of major depressive disorder; however, its unique neural mechanism is not well-understood currently. Using multimodal MRI data, this study examined common and specific alterations of amygdala subregions between patients with and without anxiety. No alterations were observed in the gray matter volume or intra-region functional integration in either patient group. Compared with the controls, both patient groups showed decreased functional connectivity between the left superficial amygdala and the left putamen, and between the (...) right superficial amygdala and the bilateral anterior cingulate cortex and medial orbitofrontal cortex, while only patients with anxiety exhibited decreased activity in the bilateral laterobasal and superficial amygdala. Moreover, the decreased activity correlated negatively with the Hamilton depression scale scores in the patients with anxiety. These findings provided insights into the pathophysiologic processes of anxious major depressive disorder and may help to develop new and effective treatment programs. (shrink)

Pei Wang, Ben Goertzel. [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [ 18] [19] [20] [21] [22] [23] [24] [25] [26] [27] Bach, J. (2009). Principles ofSynthetic Intelligence PSI: An Architecture ofMotivated Cognition (Oxford University Press,  ...

This book provides a systematic and comprehensive description of Non-Axiomatic Logic, which is the result of the author's research for about three decades.Non-Axiomatic Logic is designed to provide a uniform logical foundation for Artificial Intelligence, as well as an abstract description of the “laws of thought” followed by the human mind. Different from “mathematical” logic, where the focus is the regularity required when demonstrating mathematical conclusions, Non-Axiomatic Logic is an attempt to return to the original aim of logic, that is, (...) to formulate the regularity in actual human thinking. To achieve this goal, the logic is designed under the assumption that the system has insufficient knowledge and resources with respect to the problems to be solved, so that the “logical conclusions” are only valid with respect to the available knowledge and resources. Reasoning processes according to this logic covers cognitive functions like learning, planning, decision making, problem solving, etc.This book is written for researchers and students in Artificial Intelligence and Cognitive Science, and can be used as a textbook for courses at graduate level, or upper-level undergraduate, on Non-Axiomatic Logic. (shrink)

As many philosophers agree, the frame problem is concerned with how an agent may efficiently filter out irrelevant information in the process of problem-solving. Hence, how to solve this problem hinges on how to properly handle semantic relevance in cognitive modeling, which is an area of cognitive science that deals with simulating human's cognitive processes in a computerized model. By "semantic relevance", we mean certain inferential relations among acquired beliefs which may facilitate information retrieval and practical reasoning under certain epistemic (...) constraints, e. g., the insufficiency of knowledge, the limitation of time budget, etc. However, traditional approaches to relevance—as for example, relevance logic, the Bayesian approach, as well as Description Logic—have failed to do justice to the foregoing constraints, and in this sense, they are not proper tools for solving the frame problem/relevance problem. As we will argue in this paper, Non-Axiomatic Reasoning System (NARS) can handle the frame problem in a more proper manner, because the resulting solution seriously takes epistemic constraints on cognition as a fundamental theoretical principle. (shrink)

Every artificial-intelligence research project needs a working definition of "intelligence", on which the deepest goals and assumptions of the research are based. In the project described in the following chapters, "intelligence" is defined as the capacity to adapt under insufficient knowledge and resources. Concretely, an intelligent system should be finite and open, and should work in real time. ;If these criteria are used in the design of a reasoning system, the result is NARS, a non-axiomatic reasoning system. ;NARS uses a (...) term-oriented formal language, characterized by the use of subject-predicate sentences. The language has an experience-grounded semantics, according to which the truth value of a judgment is determined by previous experience, and the meaning of a term is determined by its relations with other terms. Several different types of uncertainty, such as randomness, fuzziness, and ignorance, can be represented in the language in a single way. ;The inference rules of NARS are based on three inheritance relations between terms. With different combinations of premises, revision, deduction, induction, abduction, exemplification, comparison, and analogy can all be carried out in a uniform format, the major difference between these types of inference being that different functions are used to calculate the truth value of the conclusion from the truth values of the premises. ;Since it has insufficient space-time resources, the system needs to distribute them among its tasks very carefully, and to dynamically adjust the distribution as the situation changes. This leads to a "controlled concurrency" control mechanism, and a "bag-based" memory organization. ;A recent implementation of the NARS model, with examples, is discussed. The system has many interesting properties that are shared by human cognition, but are absent from conventional computational models of reasoning. ;This research sheds light on several notions in artificial intelligence and cognitive science, including symbol-grounding, induction, categorization, logic, and computation. These are discussed to show the implications of the new theory of intelligence. ;Finally, the major results of the research are summarized, a preliminary evaluation of the working definition of intelligence is given, and the limitations and future extensions of the research are discussed. (shrink)

Le mot 社群 ( she qun, communauté, au sens de la Gemeinschaft allemande) n’était certes pas une problématique traditionnellement confucéenne. La compréhension éthique générale de la Chine antique reposait sur 三纲五常 ( san gang wu chang ; les trois disciplines et les cinq justes relations interpersonnelles). Les religions, associations et académies non dominantes étaient plus proches du concept de communauté. Les concepts occidentaux modernes de la sociologie ont été introduits pour la première fois en Chine à la fin du xix (...) e siècle, mais les intellectuels les comprenaient certes différemment, en fonction des valeurs traditionnelles locales, et en réponse à la nécessité de renforcer l’État chinois. L’idée moderne de communauté et le concept de société avec lequel on la contrastait n’ont été popularisés en Chine qu’à l’époque de l’industrialisation, à partir de la fin des années 1970. (shrink)

More and more packaged products in China have been labeled as low-calorie products since the official implementation of nutrition claims in 2007. But little was known about the impact of such claims on the Chinese consumption of low-calorie food on the background of increasing rates of obesity among the Chinese population. This study sought to fill the gap by applying a consumer behavior model to a nationally representative online survey by means of structural equation modeling. The findings revealed that nutrition (...) claims significantly affect the consumption of low-calorie products. Specifically, marketing stimulus on low-calorie products first affected consumer psychology, then consumer decision-making, and finally consumer responses. Despite the significant role of consumer psychology and decision-making in consumption, consumers were susceptible to the influence of targeted marketing strategies for foods with a low-calorie claim. It is recommended that appropriate use of low-calorie nutrition claims by manufacturers and choices of low-calorie food by consumers according to their own needs should be encouraged. (shrink)

Aims: To examine the extent of social stigma toward diabetes among Singapore's multi-ethnic general population and determine whether this differs across socio-demographic sub-groups.Methods: Data for this study came from a nationwide cross-sectional study. A diabetes stigma questionnaire comprising Social Distance Scale and Negative Attitudes and Stereotyping Scale was administered to those respondents who had not been diagnosed with diabetes. Exploratory factor analysis was conducted to determine the dimensionality of the instruments and validated using confirmatory factor analysis. Multiple linear regression analysis (...) was conducted to examine associations between socio-demographic factors and measures of diabetes stigma.Results: In all, 2,895 participants were recruited from the general population giving a response rate of 66.2%. Factor analyses found that a one-factor model resulted in an acceptable fit for both stigma scales, which measured social distance and negative attitudes and stereotyping, respectively. Multiple linear regression analyses identified Indian ethnicity, higher personal income and having close friends or family members who had been diagnosed with diabetes to be significantly associated with lower social distance scores while those aged 50–64 years and those with secondary and vocational education were significantly associated with higher social distance scores. Those with a personal income of SG$2,000–3,999 and SGD $6,000 and above, and those with close friends or family members diagnosed with diabetes were significantly associated with lower negative attitudes and stereotyping scores. In contrast those aged 35 years and above, those with primary education and below, and those of Malay ethnicity were significantly associated with higher negative attitudes and stereotyping scores.Conclusions: The study found a relatively low level of stigma toward diabetes in the general population of Singapore, although some stigmatizing beliefs emerged. While greater knowledge of diabetes could reduce stigma, anti-stigma messaging should be incorporated into the “War on Diabetes” programme in Singapore. (shrink)

This work aims to promote the development of the online shopping market and improve the online marketing effect of goods. First, entrepreneurial psychology and online shopping are discussed. Then, impulse buying behavior is analyzed, and the IBB model and hypotheses of consumers are proposed under the psychological model. Finally, consumers’ IBB during COVID-19 is assessed under the psychological models. Hedonic shopping value is a psychological factor directly affecting consumers’ IBB during COVID-19. The results indicate that COVID-19 has a specific stimulating (...) effect on IBB. Meanwhile, the types of goods consumers buy during COVID-19 vary widely across age groups and regions. Overall, clothing is the most purchased item by consumers. This work provides the main reference for the improvement of the online commodity marketing effect and makes a crucial contribution to the development of the online shopping market. (shrink)

The diversification of the world has given us the opportunity to live with different people. This kind of diversification brings not only adventure and excitements but also interaction with people and their habits that we do not agree with. In response, toleration has become the common sense of people in modern society. However, what is the meaning of the word toleration? What moral emotions underlie the practice of toleration? This article puts forward a morally defensible concept of toleration inspired by (...) ancient Chinese thinking. I first discuss the etymology of the word toleration from Anglophone and Chinese perspectives, and then analyse three problematical emotional attitudes towards others and critique the spirit of exclusion in the dominant Anglophone understanding of toleration. Finally, I analyse a morally defensible concept of toleration based on the ‘the dao of zhong and shu’ that also served as the ideal underpinning political unity and a... (shrink)

Intelligence can be understood as a form of rationality, in the sense that an intelligent system does its best when its knowledge and resources are insufficient with respect to the problems to be solved. The traditional models of rationality typically assume some form of sufficiency of knowledge and resources, so cannot solve many theoretical and practical problems in Artificial Intelligence (AI). New models based on the Assumption of Insufficient Knowledge and Resources (AIKR) cannot be obtained by minor revisions or extensions (...) of the traditional models, and have to be established fully according to the restrictions and freedoms provided by AIKR. The practice of NARS, an AI project, shows that such new models are feasible and promising in providing a new theoretical foundation for the study of rationality, intelligence, consciousness, and mind. (shrink)