scholarly journals Innate heuristics and fast learning support escape route selection in mice

2021 ◽  
Author(s):  
Federico Claudi ◽  
Dario Campagner ◽  
Tiago Branco
Keyword(s):  
Selection Process ◽  
Computational Modelling ◽  
Route Selection ◽  
Trial And Error ◽  
Natural Habitats ◽  
Escape Route ◽  
Fast Learning ◽  
Path Distance ◽  
Spatial Environment ◽  
Multiple Routes

When faced with imminent danger, animals must rapidly take defensive actions to reach safety. Mice can react to innately threatening stimuli in less than 250 milliseconds [1] and, in simple environments, use spatial memory to quickly escape to shelter [2,3]. Natural habitats, however, often offer multiple routes to safety which animals must rapidly identify and choose from to maximize the chances of survival [4]. This is challenging because while rodents can learn to navigate complex mazes to obtain rewards [5,6], learning the value of different routes through trial-and-error during escape from threat would likely be deadly. Here we have investigated how mice learn to choose between different escape routes to shelter. By using environments with paths to shelter of varying length and geometry we find that mice prefer options that minimize both path distance and path angle relative to the shelter. This choice strategy is already present during the first threat encounter and after only ~10 minutes of exploration in a novel environment, indicating that route selection does not require experience of escaping. Instead, an innate heuristic is used to assign threat survival value to alternative paths after rapidly learning the spatial environment. This route selection process is flexible and allows quick adaptation to arenas with dynamic geometries. Computational modelling of different classes of reinforcement learning agents shows that the observed behavior can be replicated by model-based agents acting in an environment where the shelter location is rewarding during exploration. These results show that mice combine fast spatial learning with innate heuristics to choose escape routes with the highest survival value. They further suggest that integrating priors acquired through evolution with knowledge learned from experience supports adaptation to changing environments while minimizing the need for trial-and-error when the errors are very costly.

The Road Not Taken: How Early Landscape Learning and Adoption of a Risk-Averse Strategy Influenced Paleoindian Travel Route Decision Making in the Upper Ohio Valley

2020 ◽  
Vol 86 (1) ◽  
pp. 133-152
Author(s):  
Matthew P. Purtill
Keyword(s):  
Time Allocation ◽  
Selection Process ◽  
Sampling Bias ◽  
Ohio River ◽  
Risk Averse ◽  
Ohio Valley ◽  
The Road ◽  
Archaeological Data ◽  
Risk Sensitive ◽  
Path Distance

To evaluate a model of the travel-route selection process for upper Ohio Valley Paleoindian foragers (13,500–11,400 cal BP), this study investigates archaeological data through the theoretical framework of landscape learning and risk-sensitive analysis. Following initial trail placement adjacent to a highly visible escarpment landform, Paleoindians adopted a risk-averse strategy to minimize travel outcome variability when wayfaring between Sandy Springs, a significant Ohio River Paleoindian site, and Upper Mercer–Vanport chert quarries of east-central Ohio. Although a least-cost analysis indicates an optimal route through the lower Scioto Valley, archaeological evidence for this path is lacking. Geomorphic and archaeological data further suggest that site absence in the lower Scioto Valley is not entirely due to sampling bias. Instead, evidence indicates that Paleoindians preferred travel within the Ohio Brush Creek–Baker's Fork valley despite its longer path distance through more rugged, constricted terrain. Potential travel through the lower Scioto Valley hypothesizes high outcome variability due to the stochastic nature of the late Pleistocene hydroregime. In this case, perceived outcome variability appears more influential in determining travel-route decisions among Paleoindians than direct efforts to reduce energy and time allocation.

Route Selection for Project Success: Addressing “Feeling/Perception” Issues

1998 ◽  
Author(s):  
M. Mohitpour ◽  
G. Von Bassenheim ◽  
Ardean Braun
Keyword(s):  
New Technologies ◽  
Selection Process ◽  
Cost Effective ◽  
Optimization Methods ◽  
Public Perceptions ◽  
Careful Consideration ◽  
Route Selection ◽  
Acceptable Solution ◽  
Pipeline Project ◽  
Selection For

Selecting a route for a pipeline right-of-way (ROW) generally consists of engineering (technical and economic), socioeconomic and biophysical components. To effectively select a route, simultaneous consideration must be given to all the components from the initiation of a project to the integration of all aspects of each throughout the route selection process. To successfully select a route which creates a win-win situation for all the stakeholders of a pipeline project, political/governmental issues, community and land owner views, public perceptions and other similar controlling factors (such as Safety, Health, Environment and Risk (SHER)) must be carefully analyzed and integrated into the process. It is the consideration of all these issues that will lead to a ROW which will provide a technically acceptable solution, which is at the same time the least expensive, economically viable and acceptable to the community it traverses. This paper will provide an overview of route selection techniques (including new technologies) used and the process generally practiced by pipeline designers, highlighting controlling issues and optimization methods that need to be utilized in order to achieve a cost effective route selection. It provides details on significant “Feeling/Perception” issues that can either thwart or, by careful consideration of these issues, lead to a successful pipeline project. An example of such a route selection process will be provided on a project located in rough and mountainous terrain, that has significant regulatory/governmental, land, environmental, indigenous and geological issues.

The modulatory influence of end-point controllability on decisions between actions

2012 ◽  
Vol 108 (6) ◽  
pp. 1764-1780 ◽  
Author(s):  
Ignasi Cos ◽  
Farid Medleg ◽  
Paul Cisek
Keyword(s):  
Selection Process ◽  
Dynamic Properties ◽  
Human Subjects ◽  
Reaching Movements ◽  
End Point ◽  
Gradual Process ◽  
Path Distance ◽  
Maximal Mobility ◽  
Motor Actions ◽  
Biomechanical Factors

Recent work has shown that human subjects are able to predict the biomechanical ease of potential reaching movements and use these predictions to influence their choices. Here, we examined how reach decisions are influenced by specific biomechanical factors related to the control of end-point stability, such as aiming accuracy or stopping control. Human subjects made free choices between two potential reaching movements that varied in terms of path distance and biomechanical cost in four separate blocks that additionally varied two constraints: the width of the targets (narrow or wide) and the requirement of stopping in them. When movements were unconstrained (very wide targets and no requirement of stopping), subjects' choices were strongly biased toward directions aligned with the direction of maximal mobility. However, as the movements became progressively constrained, factors related to the control of the end point gained relevance, thus reducing this bias. This demonstrates that, before movement onset, constraints such as stopping and aiming participate in a remarkably adaptive and flexible action selection process that trades off the advantage of moving along directions of maximal mobility for unconstrained movements against exploiting biomechanical anisotropies to facilitate control of end-point stability whenever the movement constraints require it. These results support a view of decision making between motor actions as a highly context-dependent gradual process in which the subjective desirability of potential actions is influenced by their dynamic properties in relation to the intrinsic properties of the motor apparatus.

VEGFRs and Notch: a dynamic collaboration in vascular patterning

2009 ◽  
Vol 37 (6) ◽  
pp. 1233-1236 ◽  
Author(s):  
Lars Jakobsson ◽  
Katie Bentley ◽  
Holger Gerhardt
Keyword(s):  
Selection Process ◽  
Cell Formation ◽  
Computational Modelling ◽  
Stalk Cell ◽  
Cell Phenotype ◽  
Vegf Receptor ◽  
Cellular Mechanisms ◽  
Dynamic Interactions ◽  
Receptor System ◽  
Molecular Control

ECs (endothelial cells) in the developing vasculature are heterogeneous in morphology, function and gene expression. Inter-endothelial signalling via Dll4 (Delta-like 4) and Notch has recently emerged as a key regulator of endothelial heterogeneity, controlling arterial cell specification and tip versus stalk cell selection. During sprouting angiogenesis, tip cell formation is the default response to VEGF (vascular endothelial growth factor), whereas the stalk cell phenotype is acquired through Dll4/Notch-mediated lateral inhibition. Precisely how Notch signalling represses stalk cells from becoming tip cells remains unclear. Multiple components of the VEGFR (VEGF receptor) system are regulated by Notch, suggesting that quantitative differences in protein expression between adjacent ECs may provide key features in the formation of a functional vasculature. Computational modelling of this selection process in iterations, with experimental observation and validation greatly facilitates our understanding of the integrated processes at the systems level. We anticipate that the study of mosaic vascular beds of genetically modified ECs in dynamic interactions with wild-type ECs will provide a powerful tool for the investigation of the molecular control and cellular mechanisms of EC specification.

scholarly journals An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences

2017 ◽  
Vol 73 (8) ◽  
pp. 628-640 ◽  
Author(s):  
Su Datt Lam ◽  
Sayoni Das ◽  
Ian Sillitoe ◽  
Christine Orengo
Keyword(s):  
Large Scale ◽  
High Efficiency ◽  
Selection Process ◽  
Low Cost ◽  
Computational Modelling ◽  
Protein Domain ◽  
Genome Sequences ◽  
Comparative Modelling ◽  
Scale Modelling ◽  
Recent Developments

Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, reviews recent developments and describes resources dedicated to large-scale comparative modelling of genome sequences. The value of subclustering protein domain superfamilies to guide the template-selection process is investigated. Some recent cases in which structural modelling has aided experimental work to determine very large macromolecular complexes are also cited.

scholarly journals Meteorological Navigation by Integrating Metocean Forecast Data and Ship Performance Models into an ECDIS-like e-Navigation Prototype Interface

2021 ◽  
Vol 9 (5) ◽  
pp. 502
Author(s):  
Andrea Orlandi ◽  
Andrea Cappugi ◽  
Riccardo Mari ◽  
Francesco Pasi ◽  
Alberto Ortolani
Keyword(s):  
Performance Indicators ◽  
Selection Process ◽  
Route Planning ◽  
Route Optimization ◽  
Prototype System ◽  
Route Selection ◽  
Complex Processes ◽  
Specific Performance ◽  
Forecast Data ◽  
Ship Performance

In the complex processes of route planning, voyage monitoring, and post-voyage analysis, a key element is the capability of merging metocean forecast data with the available knowledge of ship responses in the encountered environmental conditions. In this context, a prototype system has been implemented capable of integrating metocean models forecasts with ship specific performance data and models. The work is based on the exploitation of an open source ECDIS-like system originally developed in the e-Navigation framework. The resulting prototype system allows the uploading and visualization of metocean data, the consequent computation of fuel consumption along each analyzed route, and the evaluation of the encountered meteo-marine conditions on each route way point. This allows us to “effectively and deeply dig inside” the various layers of available metocean forecast data regarding atmospheric and marine conditions and evaluating their effects on ship performance indicators. The system could also be used to trigger route optimization algorithms and subsequently evaluate the results. All these functionalities are tailored in order to facilitate the “what-if” analysis in the route selection process performed by deck officers. Many of the added functionalities can be utilized also in a shore-based fleet monitoring and management center. A description is given of the modeling and visualization approaches that have been implemented. Their potentialities are illustrated through the discussion of some examples in Mediterranean navigation.

scholarly journals Optimal Route Maintenance based on Adaptive Equilibrium Optimization and GTA based Route Discovery Model in MANET

2021 ◽  
Author(s):  
R Hemalatha ◽  
R Umamaheswari ◽  
S Jothi
Keyword(s):  
Loss Rate ◽  
Packet Transmission ◽  
Delivery Ratio ◽  
Route Discovery ◽  
Route Selection ◽  
Optimal Route ◽  
Trust Evaluation ◽  
Route Maintenance ◽  
Multiple Routes ◽  
Maintenance Process

Abstract Recently, routing is considered the main problem in MANET due to its dynamic nature. The route discovery and the optimal route selection from the multiple routes are established for the efficient routing in MANET. The major objective of this research is to select the optimal route for packet transmission in MANET. In this paper, four stages namely trust evaluation, route discovery, optmal route selection and route maintanance are elucidated. Initially, the trust evaluation is made by using ANFIS where the primary trust values are evaluated. The next stage is the route discovery scheme, in which the routes are established by Group teaching optimization algorithm (GTA). From the route discovery scheme, multiple routes are found. The optimal route for the transmission is selected with the help of the Adaptive equilibrium optimizer (AO) algorithm. Finally, the route maintenance process is established; if any of the routes fails for the broadcast it immediately selects the alternate optimal route from the multi-zone routing table for efficient packet transmission. The proposed approach is evaluated by various performance measures like throughput, energy consumption, packet delivery ratio, end-to-end delay, packet loss rate, detection rate, and routing overhead. This result describes that the proposed approach outperforms other state-of-art approaches.

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