Beyond design: cybernetics,biological computers and hylozoism

The history of British cybernetics offers us a different form of science and engineering, one that does not seek to dominate nature through knowledge. I want to say that one can distinguish two different paradigms in the history of science and technology: the one that Heidegger despised, which we could call the Modern paradigm, and another, cybernetic, nonModern, paradigm that he might have approved of. This essay focusses on work in the 1950s and early 1960s by two of Britain’s leading cyberneticians, Stafford Beer and Gordon Pask, in the field of what one can call biological computing. My object is to get as clear as I can on what Beer and Pask were up to. At the end, I will discuss Beer’s hylozoist ontology of matter, mind and spirit. This material is not easy to get the hang of—but that is what one should expect from an unfamiliar paradigm. Presented at an international conference on the philosophy of technology, Copenhagen, 13–15 Oct 2005. Revised for submission to Synthese.     

The performance space measurement of regional innovation system based on neuropsychology

In this paper, the performance space measurement of regional innovation system was studied based on neuropsychology. Firstly, the neuropsychology and neural evolution theory were elaborated. Secondly, the genetic algorithm was used to design a regional enterprise performance space measurement model, and this was obtained by connecting the ERP production module and RBF neural network order forecast module. Finally, the algorithm and model constructed in this paper were used to predict the performance of regional foreign trade innovation system. Then, it is concluded that the model constructed in this paper includes the network with the lowest network structure complexity, the smallest training error and the least test error. Therefore, based on this premise, a good neural network that meets the actual needs of users can be obtained, which indicates that the improved method based on evolutionary neural network is effective to measure the performance of regional innovation system.     

From cybernetics to brain theory,and more: A memoir

While structured as an autobiography, this memoir exemplifies ways in which classic contributions to cybernetics (e.g., by Wiener, McCulloch & Pitts, and von Neumann) have fed into a diversity of current research areas, including the mathematical theory of systems and computation, artificial intelligence and robotics, computational neuroscience, linguistics, and cognitive science. The challenges of brain theory receive special emphasis. Action-oriented perception and schema theory complement neural network modeling in analyzing cerebral cortex, cerebellum, hippocampus, and basal ganglia. Comparative studies of frog, rat, monkey, ape and human not only deepen insights into the human brain but also ground an EvoDevoSocio view of “how the brain got language.” The rapprochement between neuroscience and architecture provides a recent challenge. The essay also assesses some of the social and theological implications of this broad perspective.     

Research and application of virtual user context information security strategy based on group intelligent computing

This article first introduced the current technology of the privacy protection model, and analyzed their characteristics and deficiencies. Afterwards, from the point of view of revenue, the shortcomings of the traditional privacy protection model have analyzed through the group intelligent computing method. Based on this, this paper proposes a research and application of virtual user information of security strategy based on group intelligent computing, through the collection of visitor's private information historical access data, intelligent calculation of the strategy group between the visitor and the interviewee. The setting of the threshold of the visited person can protect the privacy information of the user more effectively. In this paper, the implementation flow, algorithm implementation process, and specific architecture design of the proposed virtual user of privacy protection model based on group intelligent computing are introduced respectively. The specific algorithms include PCA, BP neural network, and genetic algorithm. Finally, the proposed privacy has verified through experiments. Protection model can protect user privacy more effectively than traditional privacy protection model. In the future, we will further expand and improve the privacy protection model of virtual users based on group intelligent computing, including considering the dynamic and inconsistency of access to the privacy information, that is, accessing different private information will produce different overlay effects and parallelism. We will also study how to apply this model to actual systems such as shopping websites and social platforms, and use commercial data to evaluate the performance of the model and further improve it.     

Conceptual blending of high-level features and data-driven salience computation in melodic generation

Conceptual Blending (CB) theory describes the cognitive mechanisms underlying the way humans process the emergence of new conceptual spaces by blending two input spaces. CB theory has been primarily used as a method for interpreting creative artefacts, while recently it has been utilised in the context of computational creativity for algorithmic invention of new concepts. Examples in the domain of music include the employment of CB interpretatively as a tool to explain musical semantic structures based on lyrics of songs or on the relations between body gestures and music structures. Recent work on generative applications of CB has shown that proper low-level representation of the input spaces allows the generation of consistent and sometimes surprising blends. However, blending high-level features (as discussed in the interpretative studies) of music explicitly, is hardly feasible with mere low-level representation of objects. Additionally, selecting features that are more salient in the context of two input spaces and relevant background knowledge and should, thus, be preserved and integrated in new interesting blends has not yet been tackled in a cognitively pertinent manner. The paper at hand proposes a novel approach to generating new material that allows blending high-level features by combining low-level structures, based on statistically computed salience values for each high-level feature extracted from data. The proposed framework is applied to a basic but, at the same time, complicated field of music, namely melodic generation. The examples presented herein allow an insightful examination of what the proposed approach does, revealing new possibilities and prospects.     

Contextual cueing based on specific and categorical properties of the environment

Theories of visual search have generally assumed that rejected distractors are marked so as to avoid further processing of these items (memory-driven search). To test this assumption, Horowitz and Wolfe (1998) developed the randomized search paradigm, in which standard static search is compared to dynamic search where items are randomly replotted at new locations throughout a trial. Memory-driven search predicts that search slopes should double in the dynamic condition. After reviewing earlier findings that slopes were similar in the two conditions, we present two new experiments. Experiment 1 replicated and extended our previous findings using a larger range of set sizes, a slower rate of change, and adding a fixed location dynamic condition. Experiment 2 employed stimuli that required overt fixation. Neither experiment showed evidence for memory-driven search. We conclude that visual search is best understood as a series of successive judgements of the momentary probability of target presence.     

Mate-selection and the Dark Triad: Facilitating a short-term mating strategy and creating a volatile environment

The current study (N = 242) seeks to establish the relationship between traits known collectively as the Dark Triad - narcissism, psychopathy, Machiavellianism - and mating standards and preferences. Using a budget-allocation task, we correlated scores on the Dark Triad traits with mate preferences for a long-term and short-term mate. Men scoring high on the Dark Triad may be more indiscriminate than most when selecting for short-term mates in order to widen their prospects. Furthermore, those high on the Dark Triad - psychopathy in particular - tend to select for mates based on self-interest, assortative mating, or a predilection for volatile environments. We assessed these correlations when controlling for the Big Five and the sex of the participant. We also tested for moderation by the sex of the participant and mating context. Ramifications and future directions are considered.     

基于心灵知觉理论的AI服务用户接受机制及使用促进策略

许多企业采用人工智能服务应答顾客需求,然而多项研究指出用户并不总是对此感到满意。本研究围绕着用户对AI的心灵知觉的产生和影响,探索了驱动用户对AI服务态度的关键因素及使用促进策略,包括(1)机理分析层面：用户与AI早期接触的线索和体验因素如何使得人们产生了AI“擅长计算却缺乏感受”的心灵知觉？(2)调节作用层面：不同的用户内部状态和AI外部特征怎样调节了这种心灵知觉的形成和激活？(3)促进策略层面：将AI拟动物化和提供技术援助为何能借助心灵知觉使得用户在更广泛的场景中接受来自AI的服务？本研究试图在学理层面构建一个基于心灵知觉理论的新型AI服务接受模型,为从理论上解释用户对AI服务的矛盾态度提供心理学参考;同时试图在实践层面上借助心灵知觉理论提出两种促进用户接受AI服务的路径方法,为企业在服务中提升AI的应用效能提供技术参考。     

Reaching long-term goals based on local interaction between an organism and the environment: computer simulations based on adaptive behavior

An agent-based computer simulation created using the adaptive-behavior approach has shown that in some cases it is possible to reach a long-term goal (defined here as a desirable place far removed from the agent in time and in space) without necessarily having an exhaustive, predefined plan of action, but rather by using a set of rules on sensorimotor couplings that govern the organism's local interaction with its environment. We used an agent-based simulation program that emulated a two-dimensional microworld in which agents interacted with their environment and other agents through a set of sensorimotor couplings to reach a long-term goal. The main hypothesis was that the sensorimotor coupling, which consisted of following other agents, led to the emergence of collective behavior that enabled the agents to attain the long-term goal. We systematically varied the sensorimotor couplings that allowed agents to follow other agents, agents' perceptual field length, and the number of obstacles. In total, there were 160 independent simulations for each design cell. Analysis supported the hypothesis and suggested that, in addition to the process of reaching long-term goals, other cognitive processes, such as categorization, memory, and reasoning, can be reconsidered bearing in mind the emergence of behavior and an approach based on interaction between the organism and its environment.     

Risk assessment of knowledge fusion in an innovation ecosystem based on a GA-BP neural network

The risk assessment of knowledge fusion in innovation ecosystems is directly related to these ecosystems’ success or failure. A back-propagation (BP) neural network optimized by a genetic algorithm (GA) is thus proposed to evaluate the risk of knowledge fusion in innovation ecosystems. First, an index system is constructed for evaluating the risk of knowledge fusion in innovation ecosystems, and data are collected by questionnaire for use as training data for the neural networks. To realize machine learning, 84 datasets were generated, of which 60 were used to train the network, and 24 were used to test the network in MATLAB (R2014b). Evaluation models were then constructed by the BP neural network and GA-BP neural network, and their accuracy was judged by comparing the evaluation value with the target value. The comparison shows that the GA-BP neural network has faster convergence speed and higher stability, can achieve the goal more often, and reduces the possibility of the BP neural network falling into a local optimum instead of reaching global optimization. The GA-BP neural network model for the knowledge fusion risk assessment of innovation ecosystems provides a new method for practice.     

双模态情感分析的弹幕网络视频平台营销策略

随着互联网飞跃发展, 弹幕视频应运而生。这种新型的用户与视频交互方式具有新特性, 如用户情感表达实时动态性、情感分布多峰性。同时, 新特性也给实际研究工作带来挑战, 如用户画像刻画难度增大, 视频推荐和广告推送所需精度提高。现有研究尚未对弹幕视频的新特性进行深入分析, 也没有充分挖掘其本身所蕴含的学术研究价值。本文利用深度学习、自然语言处理技术、系统动力学方法, 结合心理学、市场营销学等多学科交叉前沿知识, 从数据驱动角度对弹幕视频数据进行分析和建模, 深度挖掘视频大数据潜在的商业价值。重点研究弹幕与视频双模态融合的情感识别方法; 构建带有用户情感特征的动态用户画像, 并建立基于用户画像的网络视频粘性营销机制; 分析用户情感与视频广告插播方式的相关性, 提出视频广告动态插播策略。丰富现有研究的同时, 为网络视频企业准确定位与分析用户需求, 创建高品质的智能营销平台供理论与决策支持。     

Potentiation, overshadowing, and blocking of spatial learning based on the shape of the environment

Rats were trained in Experiment 1 to find a submerged platform in 1 corner of either a rectangular or a kite-shaped pool. When the walls creating this corner were a different color than the opposite walls, then learning about the shape of the pool was potentiated in the kite but not in the rectangle. Experiments 2-4 revealed that learning about the rectangle can be overshadowed and blocked when information about the wall color indicates the location of the platform. The results mimic findings that have been obtained with Pavlovian conditioning, and they challenge the claim that learning about the shape of the environment takes places in a dedicated geometric module.     

Influence of a beacon on spatial learning based on the shape of the test environment.

In 5 experiments rats were required to escape from a triangular shaped pool by swimming to a submerged platform. The principal group of interest in each experiment received training with a beacon attached to the platform. The purpose of the experiments was to assess if the beacon overshadowed (Experiments 1-4) or blocked (Experiment 5) learning about the position of the platform with reference to the shape of the pool. The platform was located in the center of the pool for the first 2 experiments and in a corner for the remaining experiments. Although there was an overshadowing effect in Experiment 1, the remaining experiments failed to reveal any disruptive influence of the beacon on learning based on the shape of the pool. Moreover, in Experiments 3-5 there was an indication that the beacon facilitated such learning. The results suggest that spatial learning based on the shape of a test environment may not take place in the same way as that based on more discrete landmarks.     

基于用户动态信息加工的信息流广告回避机制与重定向策略

信息流广告飞速发展的同时用户广告回避愈发普遍,然而传统广告回避结论无法平移到该情境。本研究基于用户动态的信息加工视角,试图探讨(1)动态信息加工状态下(收敛式vs发散式)产生广告屏蔽和广告跳过行为的内在机制;(2)采用归因引导重定向策略,挖掘用户屏蔽广告的“残留效应”所带来的信号价值;(3)采用广告凸显重定向策略,突破用户跳过广告的“学习效应”造成的负面影响。丰富现有理论的同时,为信息流广告的响应式优化提供理论和决策支持。     

医疗机器人的伦理风险与治理探析——基于“医−患−机”分析框架

基于“医−患−机”分析框架,医疗机器人的不断发展面临主体资质复杂、责任认定困难等责任伦理风险,医患关系重构、医患信任危机等医患伦理风险,数据质量与数据隐私等数据伦理风险,算法安全与算法偏见等算法伦理风险以及医疗资源分配正义风险。医疗机器人的伦理治理要以医学伦理和机器人伦理准则为依据,建立多元伦理治理体制,推动学术共同体的构建,探索自愿型、调节型与管制型等伦理治理工具的组合运用,加快医疗机器人伦理治理的法治化发展。

     

Failure of a landmark to restrict spatial learning based on the shape of the environment

Rats were required to find a submerged platform in the corner of a swimming pool with a distinctive shape. A landmark near the platform did not interfere with the control acquired by the pool's shape over searching for the platform. This outcome was observed with an overshadowing and a blocking design. A comparison of the ease with which the landmark and the pool's shape gained control over searching for the platform indicates that the failure of overshadowing and blocking was not a consequence of the landmark being less salient than the shape of the pool. The results are not readily explained by theories of associative learning, but they are consistent with the claim that learning about the shape of the environment takes place in a dedicated module, which excludes information about the significance of individual landmarks.     

Effects of time pressure on strategy selection and strategy execution in forced choice tests

We examined the effects of cognitive load on the strategy selection in the forced choice test (FCT) when used to detect hidden crime knowledge. Examinees (N = 120) with and without concealed knowledge from a mock crime were subjected to an FCT either under standard circumstances or cognitive load. Cognitive load was implemented through time pressure. The FCT distinguished examinees with concealed knowledge from those without better than chance in both conditions, but the counterstrategies did not differ between conditions. Further investigation revealed that time pressure did affect examinees' ability to follow their intended counterstrategy to produce randomized test patterns, which constitutes an effective counterstrategy in the FCT. Hence, time pressure lowered the success rate of effective counterstrategies, but not their incident rates. Further disambiguation of various cognitive load manipulations and their effects on strategy selection and execution is needed.     

The Live Outdoor Webcams and the Construction of Virtual Geography

The live outdoor webcam seems inseparable from the mid-1990s’ popular proliferation of the Internet. Combining a well-known medium, i.e. the photograph, with a new one, i.e. the Internet, the live outdoor webcam seems in the rear-view mirror to have contributed significantly to the popular perception of the Internet as a globally distended and thus “geographical” medium. Moreover, due to its role in the NASA Triana mission, the never-realised flagship of the Clinton–Gore administration’s Digital Earth project, the live webcam seemed to play an important part in the construction of what leading geographers coined a “virtual geography”—the geography of the Internet, and the networked geography—that sought to establish itself as a new field of study during the late 1990s. In order to substantiate for this interpretation, I would like in the first part of this article to identify a number of basic characteristics of the outdoor webcam and, in the second, to analyse and discuss two papers written by leading scholars in the field; papers which have been important in the assessment of the impact of the Internet and geographical information systems (GIS) before the scientific community as well as policy makers within technological innovation and the public sector.

Analysis of higher education and management model based on cognitive anthropology

In this paper, the application of computer technology in higher education and management mode based on cognitive anthropology was studied and a teaching recommendation method was constructed. Firstly, on the basis of the existing teaching recommendation research results, teaching recommendation was carried out by adopting the methods of linear weighting and cascade combination and combining with human social factors, geographical factors and time factors, and the validity of the results was improved. Then, the expansion was carried out in the Apache cluster environment, and the efficiency and scalability of teaching recommendation were improved, so that an innovative mode of higher education research and management was created. Experiments show that the implementation efficiency of comprehensive teaching recommendation method achieved in an Apache cluster environment is high. As the amount of data increases, the efficiency advantages become more pronounced.