scholarly journals Which one is better: Assessment and Locomotion imitation strategies in Changing Environments

2021 ◽  
Vol 2113 (1) ◽  
pp. 012034
Author(s):  
Cunying Chen ◽  
Hua Zhang
Keyword(s):  
Computational Model ◽  
Performance Feedback ◽  
Environmental Changes ◽  
Self Regulation ◽  
Dynamic Environments ◽  
Uncertain Environments ◽  
Mode Theory ◽  
Changing Environments ◽  
Regulatory Mode

Abstract Imitation is ubiquitous, yet what self-regulation orientations’ role played in imitation strategies is poorly understood, which is particularly challenging in dynamic and uncertain environments. According to regulatory mode theory, we model two imitation strategies: assessment and locomotion. Assessment pays more attention on comparation among different alternatives, they repeatedly measure, evaluate, and compare desired means and try to find out the ‘best’ one. Contrariwise locomotion refers to ‘keep moving’, once choosing one alternative, they change some choices and learn from the resulting performance feedback. Using a computational model, we explore the performance implications of dynamic environments for these two imitation strategies. Consequently, when environment is stable, assessment is more effective in maintaining the lead, whereas locomotion prevails as environmental changes become more frequent and substantial. We contribute to the literatures on strategy, imitation, and NK studies.

scholarly journals Tuning environmental timescales to evolve and maintain generalists

2020 ◽  
Vol 117 (23) ◽  
pp. 12693-12699 ◽  
Author(s):  
Vedant Sachdeva ◽  
Kabir Husain ◽  
Jiming Sheng ◽  
Shenshen Wang ◽  
Arvind Murugan
Keyword(s):  
Neutralizing Antibodies ◽  
Environmental Changes ◽  
Dynamic Environments ◽  
Affinity Maturation ◽  
Natural Environments ◽  
Broadly Neutralizing Antibodies ◽  
Complex Dynamic ◽  
Changing Environments ◽  
Cell Affinity ◽  
Do So

Natural environments can present diverse challenges, but some genotypes remain fit across many environments. Such “generalists” can be hard to evolve, outcompeted by specialists fitter in any particular environment. Here, inspired by the search for broadly neutralizing antibodies during B cell affinity maturation, we demonstrate that environmental changes on an intermediate timescale can reliably evolve generalists, even when faster or slower environmental changes are unable to do so. We find that changing environments on timescales comparable with evolutionary transients in a population enhance the rate of evolving generalists from specialists, without enhancing the reverse process. The yield of generalists is further increased in more complex dynamic environments, such as a “chirp” of increasing frequency. Our work offers design principles for how nonequilibrium fitness “seascapes” can dynamically funnel populations to genotypes unobtainable in static environments.

scholarly journals More than a snapshot: dynamic value-in-use emergence in e-services

2021 ◽  
Author(s):  
Nicole Bulawa ◽  
Frank Jacob
Keyword(s):  
Language Learning ◽  
Self Regulation ◽  
Qualitative Approach ◽  
Discrete Events ◽  
Mode Theory ◽  
Regulatory Mode ◽  
Dynamic Perspective ◽  
Empirical Context ◽  
Over Time ◽  
Static Concept

AbstractSupporting consumers’ value-in-use (ViU) emergence throughout a usage process has become increasingly challenging as, in today’s environment, usage has shifted from discrete events to continuous e-service interactions. Although researchers acknowledge that ViU is dynamic and evolves over time, most studies treat it as a static concept. Using the empirical context of language learning applications, the authors adopt a dynamic perspective on e-service ViU and extend it with regulatory mode theory using a qualitative approach. By applying the underlying functions of self-regulation: locomotion and assessment, the authors investigate how ViU emerges throughout a usage process and establish an eight-stage ViU emergence process, ranging from initial trigger to termination. By examining a consumer’s usage, assessments, and movements, practitioners can pinpoint a consumer’s location in the ViU emergence process and take appropriate measures to further promote ViU emergence in e-services.

Evolving Learnable Neural Networks Under Changing Environments with Various Rates of Inheritance of Acquired Characters: Comparison of Darwinian and Lamarckian Evolution

1999 ◽  
Vol 5 (3) ◽  
pp. 203-223 ◽  
Author(s):  
Takahiro Sasaki ◽  
Mario Tokoro
Keyword(s):  
Neural Networks ◽  
Environmental Changes ◽  
Dynamic Environments ◽  
Abstract Model ◽  
Changing Environments ◽  
Lamarckian Evolution ◽  
Inheritance Of Acquired Characters ◽  
Acquired Characters ◽  
Successive Generations ◽  
The Relationship

The processes of adaptation in natural organisms consist of two complementary phases: learning, occurring within each individual's lifetime, and evolution, occurring over successive generations of the population. In this article, we study the relationship between learning and evolution in a simple abstract model, where neural networks capable of learning are evolved using genetic algorithms (GAs). Individuals try to maximize their life energy by learning certain rules that distinguish between two groups of materials: food and poison. The connective weights of individuals' neural networks undergo modification, that is, certain characters will be acquired, through their lifetime learning. By setting various rates for the heritability of acquired characters, which is a motive force of Lamarckian evolution, we observe adaptational processes of populations over successive generations. Paying particular attention to behaviors under changing environments, we show the following results. Populations with lower rates of heritability not only show more stable behavior against environmental changes, but also maintain greater adaptability with respect to such changing environments. Consequently, the population with zero heritability, that is, the Darwinian population, attains the highest level of adaptation to dynamic environments.

scholarly journals Precise regulation of the relative rates of surface area and volume synthesis in bacterial cells growing in dynamic environments

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Handuo Shi ◽  
Yan Hu ◽  
Pascal D. Odermatt ◽  
Carlos G. Gonzalez ◽  
Lichao Zhang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Time Delay ◽  
Surface Area ◽  
Environmental Changes ◽  
Volume Ratio ◽  
Dynamic Environments ◽  
Bacterial Cells ◽  
Bacterial Growth Rate ◽  
State Size ◽  
Insight Into

AbstractThe steady-state size of bacterial cells correlates with nutrient-determined growth rate. Here, we explore how rod-shaped bacterial cells regulate their morphology during rapid environmental changes. We quantify cellular dimensions throughout passage cycles of stationary-phase cells diluted into fresh medium and grown back to saturation. We find that cells exhibit characteristic dynamics in surface area to volume ratio (SA/V), which are conserved across genetic and chemical perturbations as well as across species and growth temperatures. A mathematical model with a single fitting parameter (the time delay between surface and volume synthesis) is quantitatively consistent with our SA/V experimental observations. The model supports that this time delay is due to differential expression of volume and surface-related genes, and that the first division after dilution occurs at a tightly controlled SA/V. Our minimal model thus provides insight into the connections between bacterial growth rate and cell shape in dynamic environments.

scholarly journals The mediating role of narcissism in the effects of regulatory mode on positivity

2021 ◽  
Author(s):  
Daniela Di Santo ◽  
Calogero Lo Destro ◽  
Conrad Baldner ◽  
Alessandra Talamo ◽  
Cristina Cabras ◽  
...  
Keyword(s):  
Self Regulation ◽  
Well Being ◽  
Cross Sectional Study ◽  
Motivational Orientation ◽  
Cross Sectional ◽  
Mediating Role ◽  
Regulatory Mode ◽  
The Individual ◽  
Reported Data

AbstractPositivity (i.e., the individual tendency to positively approach life experiences) has proven to be an effective construct applied in positive psychology. However, individuals’ self-regulation may have contrasting effects on positivity. We specifically examined whether positivity could be partially explained through two aspects of motivation concerned with self-regulation: locomotion (i.e., a motivational orientation concerned with movement) and assessment (i.e., a motivational orientation concerned with comparison and evaluation). Furthermore, based on previous literature that found a link between these aspects and narcissism, we examined whether “adaptive” and “maladaptive” dimensions of narcissism could mediate the effects of locomotion and assessment on increased or decreased positivity. Narcissism was defined by previous research as adaptive or maladaptive insofar as it leads or does not lead to increased psychological well-being. We estimated a mediation model with multiple independent variables and multiple mediators in a cross-sectional study with self-reported data from 190 university students. We found that both locomotion and assessment were associated with adaptive narcissism, which in turn was positively associated with positivity. However, assessment was also associated with maladaptive narcissism, which in turn was negatively associated with positivity. Relationships between aspects of self-regulation, narcissism, and positivity can have significant implications which will be discussed.

Real Time, Near-Optimal Trajectory Planning of an Omni-Directional Vehicle

2001 ◽  
Author(s):  
Tamás Kalmár-Nagy ◽  
Pritam Ganguly ◽  
Raffaello D’Andrea
Keyword(s):  
Real Time ◽  
Optimal Trajectory ◽  
Degrees Of Freedom ◽  
Dynamic Environments ◽  
Real Time Control ◽  
Uncertain Environments ◽  
Time Control ◽  
Innovative Method ◽  
Optimal Trajectory Planning ◽  
Three Degrees Of Freedom

Abstract In this paper, we discuss an innovative method of generating near-optimal trajectories for a robot with omni-directional drive capabilities, taking into account the dynamics of the actuators and the system. The relaxation of optimality results in immense computational savings, critical in dynamic environments. In particular, a decoupling strategy for each of the three degrees of freedom of the vehicle is presented, along with a method for coordinating the degrees of freedom. A nearly optimal trajectory for the vehicle can typically be calculated in less than 1000 floating point operations, which makes it attractive for real-time control in dynamic and uncertain environments.

scholarly journals A computational model of task allocation in social insects – ecology and interactions alone can drive specialisation

2018 ◽  
Author(s):  
Rui Chen ◽  
Bernd Meyer ◽  
Julian García
Keyword(s):  
Computational Model ◽  
Social Interactions ◽  
Task Allocation ◽  
Social Insect ◽  
Group Performance ◽  
Dynamic Environments ◽  
Individual Factors ◽  
Single Task ◽  
Performance Counter ◽  
Ecological Success

AbstractSocial insect colonies are capable of allocating their workforce in a decentralised fashion; addressing a variety of tasks and responding effectively to changes in the environment. This process is fundamental to their ecological success, but the mechanisms behind it remain poorly understood. While most models focus on internal and individual factors, empirical evidence highlights the importance of ecology and social interactions. To address this gap we propose a game theoretical model of task allocation. Individuals are characterised by a trait that determines how they split their energy between two prototypical tasks: foraging and regulation. To be viable, a colony needs to learn to adequately allocate its workforce between these two tasks. We study two different processes: individuals can learn relying exclusively on their own experience, or by using the experiences of others via social learning. We find that social organisation can be determined by the ecology alone, irrespective of interaction details. Weakly specialised colonies in which all individuals tend to both tasks emerge when foraging is cheap; harsher environments, on the other hand, lead to strongly specialised colonies in which each individual fully engages in a single task. We compare the outcomes of self-organised task allocation with optimal group performance. Counter to intuition, strongly specialised colonies perform suboptimally, whereas the group performance of weakly specialised colonies is closer to optimal. Social interactions lead to important differences when the colony deals with dynamic environments. Colonies whose individuals rely on their own experience are more exible when dealing with change. Our computational model is aligned with mathematical predictions in tractable limits. This different kind of model is useful in framing relevant and important empirical questions, where ecology and interactions are key elements of hypotheses and predictions.

scholarly journals Resilience in the Face of Uncertainty: Sigma Factor B Fine-Tunes Gene Expression To Support Homeostasis in Gram-Positive Bacteria

2016 ◽  
Vol 82 (15) ◽  
pp. 4456-4469 ◽  
Author(s):  
Claudia Guldimann ◽  
Kathryn J. Boor ◽  
Martin Wiedmann ◽  
Veronica Guariglia-Oropeza
Keyword(s):  
Gene Expression ◽  
Sigma Factor ◽  
Environmental Changes ◽  
Regulation Of Gene Expression ◽  
Bacterial Survival ◽  
Gram Positive ◽  
Content Type ◽  
Gram Positive Bacteria ◽  
Changing Environments ◽  
The Face

ABSTRACTGram-positive bacteria are ubiquitous and diverse microorganisms that can survive and sometimes even thrive in continuously changing environments. The key to such resilience is the ability of members of a population to respond and adjust to dynamic conditions in the environment. In bacteria, such responses and adjustments are mediated, at least in part, through appropriate changes in the bacterial transcriptome in response to the conditions encountered. Resilience is important for bacterial survival in diverse, complex, and rapidly changing environments and requires coordinated networks that integrate individual, mechanistic responses to environmental cues to enable overall metabolic homeostasis. In many Gram-positive bacteria, a key transcriptional regulator of the response to changing environmental conditions is the alternative sigma factor σB. σBhas been characterized in a subset of Gram-positive bacteria, including the generaBacillus,Listeria, andStaphylococcus. Recent insight from next-generation-sequencing results indicates that σB-dependent regulation of gene expression contributes to resilience, i.e., the coordination of complex networks responsive to environmental changes. This review explores contributions of σBto resilience inBacillus,Listeria, andStaphylococcusand illustrates recently described regulatory functions of σB.

Sign in / Sign up

Export Citation Format

Share Document