The Dynamics of Active Categorical Perception in an Evolved Model Agent

This chapter endeavors to show that there are ancient and embodied practices in many traditional societies whose shamanic expertise includes taming and transforming non-sense into meaningful experience for the individual and collective welfare. First, the notions of embodiment, sense- making, experience, and meaning are introduced and elaborated on in the context of philosophy and cognitive science. Then the concept of non-sense is analyzed by way of distinguishing four senses for it. Next is presented the case of traditional Huichol shamanism, which employs the consciousness-modifier peyote plant in its rituals, where non-sense is manifest sometimes. Last, it is argued that the shamanic expertise on sense and non-sense can be interpreted as a traditional wisdom and practice that fosters the mental health of the individual and his community.

In this paper we study the connection between the use of evaluative language and the building of both personal and social identities, from the perspective of Dynamical System Theory. We primarily discuss two issues: 1) The use of evaluation (in the sense given to the term by Alba-Juez and Thompson (forthcoming)) as a means to the construction of both individual and group identities, thus exploring how the connection between linguistic choices and social identities is shaped by interactional needs for stancetaking. In order to illustrate this connection, we examine examples of the use of evaluative language in a web social network, and we analyze some of the discourse elements showing ways of positioning that act as catalysts for the emergence of a multifactorial dynamic system of identities. 2) The consideration of Dynamical System Theory (DST) as a theoretical framework for the modeling of language and identity. Although originally a mathematical theory, DST has been adopted by cognitive science as a valid framework for the study of cognitive phenomena, on the grounds that natural cognition is a dynamical phenomenon. Within the realm of (socio) linguistics and pragmatics, this study is to a certain degree in line with some recent studies such as Gibbs (2010), Geeraerts, Kristiansen and Peirsman (2010), or Moreno Fernández (2012). Thus, we herein focus on how linguistic evaluation intervenes in the intricate dynamical system of identity, and even though we do not engage in complex mathematical disquisition, we argue that the idea and philosophical foundation underlying DST can lead us towards the ‘integration’ of the complex equation of identity construction, and that consequently the field has great potential for further research.

The author reacts to what has been written about his own book on systems theory of pastoral care by E. Hauschildt in the foregoing article. The author explains and reminds the reader about what – at least in the perspective of systems theory – theory implies and can show and what not. Systems theory works with a theory of differences, but does not describe dualities. A systems theory of pastoral care shows an affinity of pastoral care to psychotherapy, but does not construct pastoral care as if it were something therapeutic.

This article reports on a study that took a Dynamic Systems Theory (DST) perspective to second language (L2) motivational self system (L2MSS). More specifically, it investigated the influence of an Intensive English Reading course based on the Production-Oriented Approach (POA) upon the L2MSS of Chinese university English majorsfrom the DST perspective. To this end, two intact classes composed of 50 students were assigned into experimental group (EG) (N = 23) and control group (CG) (N = 27), who responded to an L2MSS scale before and after the one-semester intervention. Eight and five students were respectively selected using the purposive sampling method from the experimental and control groups for follow-up semi-structured interviews. The quantitative results revealed that the overall and dimensional (Ideal L2 Self and L2 Learning Experience) levels of L2MSS were significantly strengthened over time in the EG while kept stable in the CG. The qualitative results suggested that the enhanced Ideal L2 Self of the participants stemmed from an attractor basin that was deepened by a number of attractors encompassing Output Tasks and Peer Performance. The interview results also showed that the increased L2 Learning Experience of the participants pertained to an attractor basin that was consolidated by an array of attractors containing Output Tasks, Teacher Guidance, Group Discussion, and Peer Assessment. The findings indicated that the attractors at the subjective and social dimensions in the POA-based course collectively worked together to cause changes in L2MSS among the participants. The implications for intervening L2 motivation from a POA approach in English as a Foreign Language (EFL) classrooms were discussed.

This report details a workshop held at the Bartlett School of Architecture, University College London, to initiate interdisciplinary collaborations for the practice of systems architecture, which is a new model for the generation of sustainable architecture that combines the discipline of the study of the built environment with the scientific study of complexity, or systems science, and adopts the perspective of systems theory. Systems architecture offers new perspectives on the organization of the built environment that enable architects to consider architecture as a series of interconnected networks with embedded links into natural systems. The public workshop brought together architects and scientists working with the convergence of nanotechnology, biotechnology, information technology, and cognitive science and with living technology to investigate the possibility of a new generation of smart materials that are implied by this approach.

Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose “brain” is modeled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain), finding different behavioral strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behavior and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input. To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy of mind.

According to a brief and very general definition Cognitive Science is an interdisciplinary scientific study of how information is represented and transformed in a human nervous system. “Information”, “representation” and “transformation” are keywords here. Many disciplines bring considerable contribution to Cognitive Science. Logic is one of them. Logic investigates these rules which allow us to recognize valid reasonings and distinguish them from those that fail to fulfill the condition of validity. Thus logic investigates some representation (or representations) of reasoning. Significant part of information transformed in nervous system is related to reasoning and inference. This fact opens special perspectives on applying Logic in Cognitive Science both in representing as well as in transforming information. Any formal logical system constitutes a kind of representation of a class of propositions considered as sentence content. In this way each logical system provides a representation of a broad class of belief states. At the same time any inference relation, related to a given logical system, represents a transformation of some type of information. As a consequence it would be hard to find logical investigations which could not be applied in Cognitive Science. Such an idea guided us while we were preparing the present volume.

Contemporary challenges, stemming from accelerated digitalization and the increasing complexity of political processes, are driving the integration of interdisciplinary approaches into political science. For the first time in history, advances in neuroscience and digital technologies make it possible to probe the depths of human consciousness, enabling the analysis and prediction of behavior that circumvents an individual’s conscious will. This capability presents a fundamental challenge to the Enlightenment principle of individual sovereignty, demanding both philosophical reflection and empirical research into its profound opportunities and risks. The authors address this challenge by examining the cognitive dimensions of political decision-making, leadership, and mass belief formation. Particular attention is paid to the impact of digitalization on the transformation of political behavior and governance strategies. Drawing on findings from neurophysiology and cognitive science, the authors examine the key mechanisms that determine decision-making in the political sphere, including the influence of emotional and cognitive factors. It is argued that the integration of neuroscience and digital technologies is transforming traditional approaches to the analysis of political reality. Furthermore, the synergy between cognitive science, sociology, and political science opens new avenues for researching human potential, a critical task of particular relevance in an era of global uncertainty and digital transformation. The proposed approaches not only deepen the understanding of the cognitive and emotional mechanisms of political behavior but also facilitate the development of new tools for forecasting and governance in the contemporary political environment. The article highlights the dual nature of using the tools of political cognitive science: on the one hand, it offers unprecedented opportunities for understanding political processes; on the other, it creates risks of conscious manipulation and the erosion of human agency. The authors conclude that the development of robust ethical principles for the use of neurotechnology in politics is imperative. Such principles must be designed to enhance human potential and safeguard the role of individuals as the subjects of political development, preventing their reduction to manageable data resources.

Categorical perception, or the perceived equality of instances within a phoneme category, has been a central concept in the experimental and theoretical investigation of speech perception. It can be found as fact in most introductory textbooks in perception, cognition, linguistics and cognitive science. This paper analyzes the reasons for the persistent endurance of this concept. A variety of empirical and theoretical research findings are described in order to inform and hopefully to provide a more critical look at this pervasive concept. Given the demise of categorical perception, it is necessary to shift our theoretical focus to how multiple sources of continuous information are processed to support the perception of spoken language.

From the perspective of systems theory, human health results from a dynamic balance between environmental, biological, and behavioral factors [1]. The interaction between endocrine-disrupting chemicals (EDCs), sedentary lifestyles, ultraprocessed food consumption, and disconnection from natural stimuli disrupts circadian rhythms, metabolism, and brain functions, generating a state of neuroendocrine dysregulation and systemic inflammation [1,2]. Exposure to EDCs compromises hormonal and neurochemical regulation, with transgenerational effects that increase the risk of psychiatric and metabolic disorders in future generations, exacerbated by the role of adipose tissue as a bioaccumulator of toxins [3,4]. Emerging diseases, once exclusively associated with viral infections (such as COVID-19 and the Zika virus), now also include metabolic, neurodegenerative, and psychiatric disorders that are rapidly increasing due to circadian disruption, chronic inflammation, and loss of environmental variability [3,5,6]. These factors operate systemically, leading to neurochemical imbalances, hormonal dysfunctions, and impaired adaptive responses [7]. To counteract these effects, a systemic approach is necessary, based on circadian rhythm regulation, exposure to nature and cold, neurofeedback, functional nutrition, and hormonal balance [8]. In this context, epigenetic reprogramming emerges as a key mechanism to modulate gene expression without altering DNA, enabling the reversal of environmental damage through targeted interventions in lifestyle, diet, and neuroprotection [9]. These strategies represent a new frontier in the prevention and treatment of neuroendocrine dysfunctions and emerging diseases, laying the foundation for an integrated therapeutic paradigm adapted to the needs of modern society.

Travel time reliability (TTR) holds significant importance as an evaluation index in the transportation industry. To simplify TTR calculations at the network level in engineering applications, this paper re-examines the highway network from the perspective of system theory, regards it as a road network system consisting of multiple subsystems, and proposes a framework for calculating the TTR of the highway network based on the information entropy model. The information entropy model is employed to quantify the level of disorder within the temporal distribution, thereby substituting the need for fitting or deducing the distribution function as practiced in conventional methodologies. The design of roadway indicators considers the social attributes of the transportation network, making reliability not solely dependent on temporal data. For the case study, we used data from the electronic toll collection gantry system on the Xi’an bypass highway. The results indicate that the TTR of the inner ring within the ring network is significantly higher than that of the outer ring. Furthermore, the reliability of the network is lower than that of any sub-section, during both peak and off-peak hours. The applicability of the proposed computational framework is demonstrated and the nature of the results is explored in comparisons with traditional metrics and time prediction attempts. The approach to the TTR evaluation problem from a novel perspective presented in this research omits the procedure of fitting the time distribution function and avoids being affected by its heterogeneity, making TTR calculation and extension more efficient and convenient.

With the continuous development of social economy and the gradual improvement of people's living standards, people begin to attach great importance to their own health problems. The pursuit of a healthy life has changed dramatically from the previous treatment of diseases to the current disease free prevention. As the content of regional medical information sharing, the system construction of health archives for its security issues is in full swing, but repeated research and construction greatly waste resources and raise costs, so it is necessary to introduce domain analysis methods to reduce duplication and reduce costs. It does not simply input the contents of the paper medical records into the computer, but also records every bit of health related information in residents' daily life. Doctors can extract relevant information anytime and anywhere to quickly and comprehensively understand the situation. The retrieval is more convenient. Based on the existing research results, using the theories and methods of information ecology, from the perspective of system theory, taking the balance and sustainable development of the ecosystem as the foothold, this paper deeply studies the basic operating mechanism of the health file information ecosystem, discovers the rules from it, and provides reference for the management of the health file information system and the healthy and sustainable development of China's national health system project.

At present, the comprehensive reform in police colleges is in full swing, but there is a problem that teaching, and are separated from each other in the existing reform. From the perspective of system theory, combined with computer aided technology, the distinctive characteristics of education and reform in police colleges, this paper organically integrates the basic elements of teaching, and education and reform, and puts forward the computer aided learning management trinity joint framework and interactive effect mechanism of reform in police colleges, which reflects the integrity, relevance and hierarchical characteristics. Based on the practical work of Nanjing Forest Police College, this paper puts forward the comprehensive reform strategy of police colleges as follows: with computer aided technology, the reform of teachers' teaching should pay attention to the construction of teachers' ethics and style and improve teachers' ability, the reform of students' should pay attention to the external environment and internal training, and the reform of school should pay attention to the combination of humanism and diversification and loose management.

Crude oil and grain, as two pivotal global commodities, exhibit significant price co-movement that profoundly affects national economic stability and food security. From the perspective of systems theory, the energy and grain markets do not exist in isolation but rather form a highly coupled complex system, characterized by nonlinear feedback, cross-market risk contagion, and cascading effects. This study systematically investigates the transmission mechanisms from international crude oil prices to the domestic prices of Chinese four major grains, employing the DY spillover index, Vector Error Correction Model (VECM), and a mediation effect framework. The empirical findings reveal three key insights. First, rising international crude oil prices significantly strengthen the pass-through of global grain prices to domestic markets, while simultaneously weakening the effectiveness of domestic price stabilization policies. Second, higher crude oil prices amplify international-to-domestic price spillovers by increasing maritime freight costs, a key channel in global grain trade logistics. Third, elevated oil prices stimulate demand for renewable biofuels, including biodiesel and ethanol, thereby boosting international demand for corn and soybeans and intensifying the transmission of price fluctuations in these commodities to the domestic market. These findings reveal the key pathways through which shocks in the energy market affect food security and highlight the necessity of studying the “energy–food” coupling mechanism within a systems framework, enabling a more comprehensive understanding of cross-market risk transmission.

An investigation of the coupling coordination of a regional agricultural economics-ecology-society composite based on a data-driven approach