Cognitive Hierarchy Research Articles

Hierarchy of value orientation and beliefs in climate change influencing the farmers' extractive or non-extractive behavior on the farm.

Understanding drivers of farmers' extractive and non-extractive behavior regarding natural resources has become increasingly important in the face of anthropogenic climatic change, which is a major challenge in today's world. Non-extractive behavior on the farm refers to the use of natural resources to the extent that it is possible to renew the context and not harm nature and non-renewable resources. Extractive behavior on the farm is associated with the extensive extraction of natural resources without provision for their renewal such as digging deeper wells instead of using water optimally, using chemical fertilizers with more repetition and higher dosage instead of the bio-fertilizers, and as a later result more climate change. To successfully respond human-made climate change using a cognitive hierarchy model, the influence of values on belief and behavior was assessed by a survey method among farmers of Zanjan province, Iran. A representative sample of 265 farmers was surveyed using proportional randomized multi-stage sampling. The results revealed that value orientation significantly elucidated 21% of the variability in non-extractive behavior and 26% of extractive behavior variance in a direct way and through beliefs in climate change. The recommendations have been presented to increase farmer's efforts to reduce their ecological footprint in nature.

EXPRESS: Consciousness, (meta)Cognition, and Culture.

Our conscious experience is determined by a combination of top-down processes (e.g., prior beliefs) and bottom-up processes (e.g., sensations). The balance between these two processes depends on estimates of their reliability (precision), so that the estimate considered more reliable is given more weight. We can modify these estimates at the metacognitive level, changing the relative weights of priors and sensations. This enables us, for example, to direct our attention to weak stimuli. But there is cost to this malleability. For example, excessive weighting of top-down processes, as in schizophrenia, can lead to perceiving things that are not there and believing things that are not true.It is only at the top of the brain's cognitive hierarchy that metacognitive control becomes conscious. At this level, our beliefs concern complex, abstract entities with which we have limited direct experience. Estimates of the precision of such beliefs are more uncertain and more malleable. However, at this level we don't need to rely on our own limited experience. We can rely instead on the experiences of others. Explicit metacognition plays a unique role, enabling us to share our experiences. We acquire our beliefs about the world from our immediate social group and from our wider culture. And the same sources provide us with better estimates of the precision of these beliefs. Our confidence in our high-level beliefs is heavily influenced by culture at the expense of direct experience.

Interdicting Attack Plans with Boundedly Rational Players and Multiple Attackers: An Adversarial Risk Analysis Approach

Cybersecurity planning supports the selection of and implementation of security controls in resource-constrained settings to manage risk. Doing so requires considering adaptive adversaries with different levels of strategic sophistication in modeling efforts to support risk management. However, most models in the literature only consider rational or nonstrategic adversaries. Therefore, we study how to inform defensive decision making to mitigate the risk from boundedly rational players, with a particular focus on making integrated, interdependent planning decisions. To achieve this goal, we introduce a modeling framework for selecting a portfolio of security mitigations that interdict adversarial attack plans that uses a structured approach for risk analysis. Our approach adapts adversarial risk analysis and cognitive hierarchy theory to consider a maximum-reliability path interdiction problem with a single defender and multiple attackers who have different goals and levels of strategic sophistication. Instead of enumerating all possible attacks and defenses, we introduce a solution technique based on integer programming and approximation algorithms to iteratively solve the defender’s and attackers’ problems. A case study illustrates the proposed models and provides insights into defensive planning. Funding: A. Peper and L. A. Albert were supported in part by the National Science Foundation [Grant 2000986].

Attack Identification for Cyber-Physical Security in Dynamic Games under Cognitive Hierarchy

This paper considers the problem of identifying the profiles and capabilities of attackers injecting adversarial inputs to a cyber-physical system. The system in question interacts with attackers of different levels of intelligence, each employing different feedback controllers against the system. Principles of behavioral game theory – specifically the concept of level-k thinking – is employed to construct a database of potential attack vectors. By observing the state trajectories under sequential interactions with different adversaries, the defender adaptively estimates both the number and profiles of the different attack signals using an online deterministic annealing approach. This information is used to dynamically estimate the level of intelligence of the attackers. Simulation results showcase the efficacy of the proposed method.

Dynamic Functional Connectome Harmonics.

Functional connectivity (FC) "gradients" enable investigation of connection topography in relation to cognitive hierarchy, and yield the primary axes along which FC is organized. In this work, we employ a variant of the "gradient" approach wherein we solve for the normal modes of FC, yielding functional connectome harmonics. Until now, research in this vein has only considered static FC, neglecting the possibility that the principal axes of FC may depend on the timescale at which they are computed. Recent work suggests that momentary activation patterns, or brain states, mediate the dominant components of functional connectivity, suggesting that the principal axes may be invariant to change in timescale. In light of this, we compute functional connectome harmonics using time windows of varying lengths and demonstrate that they are stable across timescales. Our connectome harmonics correspond to meaningful brain states. The activation strength of the brain states, as well as their inter-relationships, are found to be reproducible for individuals. Further, we utilize our time-varying functional connectome harmonics to formulate a simple and elegant method for computing cortical flexibility at vertex resolution and demonstrate qualitative similarity between flexibility maps from our method and a method standard in the literature.

Analysing the Effect of Incorporating Images While Framing MCQs For Online Clinical Anatomy Assessment Among First Year Medical Students

The disruptions caused by COVID-19 pandemic has significantly affected the assessment component of the undergraduate medical curriculum. The lack of physical ascertainment of the learning outcomes has forced the medical educators across the world to adopt online modes of assessment. Though multiple options like true / false, short answers and viva were available, the most common tool for many was multiple choice questions as they could be arranged according to the cognitive hierarchy of Miller’s pyramid. The present study was undertaken to analyze the effect of incorporating images while framing MCQs for online anatomy assessment among first year medical students. The study was planned in a quasi-controlled design where a batch of 150 students were subjected to a set of 40 multiple choice questions (20 text based and 20 image based MCQs). The questions were designed following Ebel and Frisbie guidelines of MCQs and validated by three investigators independently. Three cycles of assessments were conducted, and the scores were analyzed. At the end of 3 cycles of assessment feedback was taken from the students regarding this method of assessment. The performance of students was better in image based MCQs compared to traditional MCQs in all regions. Upon documenting the percipience, students had felt that image based MCQs were interesting, improved their clinical reasoning skills, lateral thinking abilities and quest for learning applied anatomy. Thus, we postulate that image based MCQs could be considered as better assessment tool in the era of online learning KEYWORDS: Assessment, Clinical anatomy, Image based assessment, MCQs, Online learning.

Exploring Social Norms and Control Coercive on Intimate Partner Violence in the Young. Implications for Prevention.

This empirical work focuses on social norms as a way of transmitting psychological violence in young people, which could be affecting the effectiveness of preventive programs in dating violence. These programs are effective in changing beliefs, but new intervention approaches are in demand due to the former's limitations in achieving behavioral changes. The main objective of this study is to demonstrate that some dimensions of psychological violence are transmitted as a descriptive social norm, without any need of victimization. In a sample of 1,265 people (18-25 years old) and through two different studies, we explored the perception of prescriptive and descriptive social norms in situations of coercive control applied to three contexts (Study 1), isolation and domination (Study 2), under the hypothesis that coercive control is passed on as a descriptive social norm between peers. Characteristics describing diversity are taken into account. The results in frequency and Structural Equation Model analysis confirm the main hypothesis, because both perceptions are not correlated. Social norms no covariate with social characteristics. Same cannot be said of isolation and domination, leading to three conclusions for prevention. (1) Not all psychological violence works the same. Coercive control starts from a primary cognitive process that requires complementary actions, based for example on the cognitive hierarchy among social norms; (2) Preventive programs are often based on "prescribed" behaviors, related to the consequences they have on victims, whereas the descriptive social norm found in this study does not correlate with victimization, unless control is applied to specific contexts. Therefore, an additional effort in prevention could go deeper with more specific behaviors that show both the different types of psychological violence and the contexts of application; (3) Finally, at the policy level, results found call for the need for preventive efforts on psychological violence in the 18 to 25 age group and specific awareness campaigns.

Neural mechanisms underlying rule selection based on response evaluation: a near-infrared spectroscopy study

The ability of humans to use rules for organizing action demands a high level of executive control. Situational complexity mediates rule selection, from the adoption of a given rule to the selection of complex rules to achieve an appropriate response. Several rules have been proposed to be superordinate to human behavior in a cognitive hierarchy and mediated by different brain regions. In the present study, using a novel rule-selection task based on pre-response evaluations that require several cognitive operations, we examined whether the task is mediated by a specific region of the prefrontal cortex using near-infrared spectroscopy. We showed that the selection of rules, including prior evaluation of a stimulus, activates broader areas of the prefrontal and premotor regions than response selection based on a given rule. The results are discussed in terms of hierarchical cognitive models, the functional specialization of multiple-cognitive operations in the prefrontal cortex, and their contribution to a novel cognitive task.

ПРИНЦИП КОГНІТИВНОЇ ІЄРАРХІЇ ПРИ ПРИЙНЯТТІ ІНДИВІДУАЛЬНИХ ТА КОЛЕКТИВНИХ РІШЕНЬ

The purpose of this study was to analyze the methods of k-levels and cognitive hierarchy, their approbation and application to solve various problems of an individual and collective nature with the help of an applied experiment. The task was to conduct the analysis several times and in different time frames, in several iterations. Effects such as cooperation and additional information were additionally investigated since in addition to individual decision-making under conditions of asymmetric information, a second attempt was also offered, after everyone heard the winners and heard the results of the first attempt, i.e., the information was symmetrical and available to everyone. At the third attempt, it was suggested to join any groups and make collective decisions. The experiment was conducted on the basis of differently formed groups. Students of specialized fields of education of various years of study, and scientific and pedagogical workers with professional education (candidates and doctors of economic, technical, physical and mathematical sciences) were selected. Two models for k-levels, k-LR and cognitive hierarchy (CH), were chosen and built for the study. Although the models are similar, they have some differences. The goal was to compare the indicators of the models with those that will be obtained in practice, and to prove or disprove the relevance of their use in decision-making evaluation. An experiment was conducted, data were collected, and their analysis was carried out by calculating and comparing experimental and model data. As a result, it was established that the experimental results were close to the CH model and not to the k-LR model. Factors such as awareness and cooperation increased the number of higher (deeper) level players at the expense of lower-level players. Changes due to awareness or cooperation occurred, but were not significant, and only brought the experimental results closer to the point of convergence with the model ones, which once again emphasized the possibility of using this model in different circumstances. Under circumstances such as information or cooperation, no optimal solution (saddle point) was found under pure strategies, according to Nash and Pareto. This finding is especially promising for the future economic analysis since it proves that even with an obvious solution to the model, it cannot always be solved according to “classical” theories and equilibrium, and people’s behavior is described by more complex cognitive processes in decisionmaking and operations research.

Application of Bloom’s Taxonomy to Teaching Design of English for Specific Purpose

This paper aims to use Bloom's taxonomy to systematize English learning objectives and form a hierarchical structure of objectives from easy to difficult, so as to design interlocking teaching links and construct a teaching design framework that conforms to the rules of cognitive hierarchy. As an extension of English teaching on the basis of college General English, English for Specific Purpose (ESP) is generally designed to train and enhance students' ability via application of English in a certain field, closely following the actual demand of relevant tasks with language skills in the field as the core.

Spatio-Temporal Dynamics of Entropy in EEGS during Music Stimulation of Alzheimer's Disease Patients with Different Degrees of Dementia.

Music has become a common adjunctive treatment for Alzheimer’s disease (AD) in recent years. Because Alzheimer’s disease can be classified into different degrees of dementia according to its severity (mild, moderate, severe), this study is to investigate whether there are differences in brain response to music stimulation in AD patients with different degrees of dementia. Seventeen patients with mild-to-moderate dementia, sixteen patients with severe dementia, and sixteen healthy elderly participants were selected as experimental subjects. The nonlinear characteristics of electroencephalogram (EEG) signals were extracted from 64-channel EEG signals acquired before, during, and after music stimulation. The results showed the following. (1) At the temporal level, both at the whole brain area and sub-brain area levels, the EEG responses of the mild-to-moderate patients showed statistical differences from those of the severe patients (p < 0.05). The nonlinear characteristics during music stimulus, including permutation entropy (PmEn), sample entropy (SampEn), and Lempel–Ziv complexity (LZC), were significantly higher in both mild-to-moderate patients and healthy controls compared to pre-stimulation, while it was significantly lower in severe patients. (2) At the spatial level, the EEG responses of the mild-to-moderate patients and the severe patients showed statistical differences (p < 0.05), showing that as the degree of dementia progressed, fewer pairs of EEG characteristic showed significant differences among brain regions under music stimulation. In this paper, we found that AD patients with different degrees of dementia had different EEG responses to music stimulation. Our study provides a possible explanation for this discrepancy in terms of the pathological progression of AD and music cognitive hierarchy theory. Our study has adjunctive implications for clinical music therapy in AD., potentially allowing for more targeted treatment. Meanwhile, the variations in the brains of Alzheimer’s patients in response to music stimulation might be a model for investigating the neural mechanism of music perception.

Generalized Dynamic Cognitive Hierarchy Models for Strategic Driving Behavior

While there has been an increasing focus on the use of game theoretic models for autonomous driving, empirical evidence shows that there are still open questions around dealing with the challenges of common knowledge assumptions as well as modeling bounded rationality. To address some of these practical challenges, we develop a framework of generalized dynamic cognitive hierarchy for both modelling naturalistic human driving behavior as well as behavior planning for autonomous vehicles (AV). This framework is built upon a rich model of level-0 behavior through the use of automata strategies, an interpretable notion of bounded rationality through safety and maneuver satisficing, and a robust response for planning. Based on evaluation on two large naturalistic datasets as well as simulation of critical traffic scenarios, we show that i) automata strategies are well suited for level-0 behavior in a dynamic level-k framework, and ii) the proposed robust response to a heterogeneous population of strategic and non-strategic reasoners can be an effective approach for game theoretic planning in AV.

Cognitive Hierarchy and Intelligence

The article deals with the issue of the cognitive pyramid and the possible use of intelligence analysis in the context of gaining the understanding and wisdom of users of information using this pyramid. The cognitive pyramid is used to define the terms date, information, knowledge, understanding and wisdom that make up the various levels of the pyramid. The paper attempts to discuss concepts in different models of the pyramid. It briefly describes intelligence in the context of the use of intelligence by means of a cognitive pyramid. Intelligence is a special kind of knowledge. This article also seeks to explore how intelligence creation can be explained using a cognitive analytical pyramid model.

Long-range functional connections mirror and link microarchitectural and cognitive hierarchies in the human brain.

Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry. We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections. Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture. By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.

A psychological model to understand background reasons for different attitudes and behaviors of youth residents in relation to free-roaming cat problems on a human-inhabited World Heritage Island in Japan

Obtaining cooperation from the local people is a key factor in an efficient management of invasive species. However, conflicts between invasive species managers and local people occur, when the target species is strongly bonded with humans. To understand the attitudes and behaviors of local people toward the issues on free-roaming cats ( Felis silvestris catus ), we conducted a questionnaire study covering all high school students—who are important future stakeholders and could reflect ideas of their parents whose responses are hard to attain—on Tokunoshima Island, Japan, where the ecological negative impacts of free-roaming cats are exacerbated by residents’ feeding. We used a cognitive hierarchy model and structural equation modeling (SEM) to study the relations between our questionnaire items: background characteristics (i.e., cat ownership, education experience around cat-caused negative ecological impacts, attitudes and perceptions around cats and nature), perceptions of the negative cat impacts on nature and people, attitudes toward outdoor cat management, and the frequency of outdoor feeding. Results from 1162 youth respondents showed that cat owners and people who believed that cats are useful for rodent control exhibited a higher frequency of outdoor feeding, perhaps due to feeding their own cats outdoors. Perceptions on the negative impacts of cats on people (e.g., zoonoses and public nuisances) which were disagreed by cat lovers, showed a stronger effect than the perceptions of negative ecological impacts, in terms of the approval of outdoor cat management. In general, informing people about the threats of outdoor cats to people, house-owned cats and livestock through education activities regarding the cat issues will lead to a better understanding and cooperation toward outdoor cat management. Educating teenagers who are more likely to accept new knowledge is especially necessary. Keeping cats indoors and reducing the frequency of feeding outdoor cats are still one of the fundamental solutions to decrease the number of outdoor cats, which will in turn decrease the risk of cat predation on native species.

Deep Reinforcement Learning Based Game-Theoretic Decision-Making for Autonomous Vehicles

This letter presents an approach for implementing game-theoretic decision-making in combination with deep reinforcement learning to allow vehicles to make decisions at an unsignalized intersection by use of 2D Lidar to obtain their observations of the environment. The main novelty of this work is modeling multiple vehicles in a complex interaction scenario simultaneously as decision-makers with conservative, aggressive, and adaptive driving behaviors. The game model allows anticipating reactions of additional vehicles to the movements of the ego-vehicle without using any specific coordination or vehicle-to-vehicle communication. The solution of the game is based on cognitive hierarchy reasoning and it uses a deep reinforcement learning algorithm to obtain a near-optimal policy towards a specific goal in a realistic simulator (ROS-Gazebo). The trained models have been successfully tested on the simulator after training. Experiments show that the performance of the lab cars in the real-world is consistent with it in the simulation environment, which may have great significance to improve the safety of self-driving cars, as well as may reduce their dependence on road tests.

Understanding young people’s perception toward forestation as a strategy to mitigate climate change in a post-conflict developing country

Understanding the perceptions of young people is a critical issue in the formulation and implementation of climate change mitigation strategies. Based on cognitive hierarchy theory, the present study aims to investigate the factors that motivate or hinder young people’s perception of forestation as a strategy to mitigate climate change in post-conflict Somalia. This study hypothesized a model in which climate change knowledge, risk perception and forest value orientations (anthropocentric/biocentric) influence attitude toward forestation and attitude, in turn, predicts behavioral intentions. We randomly surveyed students from three universities in three different regions of Somalia and collected 434 structured survey questionnaires. Using structural equation modeling, the results showed that climate change knowledge is a significant predictor of behavioral intention but not attitude toward forestation. The results also revealed that young people’s perception toward forestation as a strategy to mitigate climate change is significantly influenced by biocentric value orientation both directly and indirectly through attitude toward forestation. Contrary to previous studies, our results indicate that attitude partially mediates the relationship between biocentric value orientation and behavioral intentions and fully mediates the relationship between anthropocentric value orientation, risk perception and behavioral intentions, while it did not show any mediation results between climate change knowledge and behavioral intention. We found that the young people’s climate action or inaction is mainly shaped by climate change knowledge, biocentric value orientation, and attitude toward forestation. Finally, climate change mitigation efforts should avoid relying solely on attitude for behavioral decision-making formation and instead incorporate other factors into a more comprehensive framework.

Examining the role of receptivity to green communication, altruism and openness to change on young consumers’ intention to purchase green apparel: A multi-analytical approach

The current study aims to examine the impact of receptivity to green communication, altruism and openness to change on young consumers' purchase intention towards green apparel in India. Using a two stage approach, the research model is assessed with data collected through an online survey from a sample of 549 young consumers. In the first step, structural equation modeling (SEM) is used to determine the linear relationship among factors in the theoretical model. In the second step, artificial neural network (ANN) analysis is used to determine the predictive accuracy of the significant factors obtained from the SEM. The results from the SEM analysis reveal that receptivity to green communication, altruism and openness to change, along with the three predictors of the theory of planned behavior (TPB) significantly affect consumers’ purchase intention towards green apparel. Further, there is an indirect effect of altruism and openness to change on purchase intention through attitude supporting the value-attitude-behavior cognitive hierarchy (VABH). Besides, perceived behavioral control is found to mediate the impact of openness to change on intention to purchase green apparel. The root mean square of error (RMSE) values obtained from the ANN analysis suggest that the models show good predictive accuracy. The study contributes to the existing literature by confirming the applicability of the TPB and the VABH as well as suggesting a robust predictive framework by using ANN for green apparel purchase intention.

Deep and shallow thinking in the long run

Humans differ in their strategic reasoning abilities and in beliefs about others' strategic reasoning abilities. Studying such cognitive hierarchies has produced new insights regarding equilibrium analysis in economics. This paper investigates the effect of cognitive hierarchies on long run behavior. Despite short run behavior being highly sensitive to variation in strategic reasoning abilities, this variation is not replicated in the long run. In particular, when generalized risk dominant strategy profiles exist, they emerge in the long run independently of the strategic reasoning abilities of players. These abilities may be arbitrarily low or high, heterogeneous across players, and evolving over time.

Early Career Researcher: From Managerial Construct to Socio-Epistemic Reality

The article presents the results of the study of young scientists (early career researchers) and their role in the functioning of research teams and the academic system. It shows why this topic has not only applied relevance connected with the theoretical justification of science policy but also concerns fundamental issues of philosophy of science. The nature of the structural organization of scientific teams and the scientific community as a whole is discussed. It is argued that science shares with other social institutions a socio-epistemic hierarchy, involving the division of participants into more and less experienced ones, performing certain functions in accordance with the available amount of knowledge and skills. It is shown that this hierarchy is supported by the system of division of labor in science, but does not lead to the formation of a rigid structure, which is reflected in the mismatch of social and cognitive hierarchies of research teams. It is also shown that the contribution of young scientists to the overall scientific result can not only be great due to the appearance of young geniuses. Scientific youth performs a number of cognitive and social functions that are system-forming and are not duplicated at other levels of the scientific hierarchy. These functions may undergo changes depending on the general state of both a separate research area and the scientific system as a whole. This makes the research of scientific youth promising for studying the transformations of science as a social institution and a cultural and historical phenomenon, in particular, for analyzing scientific communications that constitute the scientific community as a collective subject of scientific knowledge, and changes in scientific ethos.