scholarly journals Colour Discrimination From Perceived Differences by Birds

2021 ◽  
Vol 9 ◽  
Author(s):  
Jair E. Garcia ◽  
Detlef H. Rohr ◽  
Adrian G. Dyer
Keyword(s):  
Decision Making ◽  
Columba Livia ◽  
Discrimination Threshold ◽  
Spectral Information ◽  
Natural Environments ◽  
Colour Discrimination ◽  
Complex Environments ◽  
Neural Representations ◽  
Bird Vision ◽  
Colour Signals

The ability of visual generalists to see and perceive displayed colour signals is essential to understanding decision making in natural environments. Whilst modelling approaches have typically considered relatively simple physiological explanations of how colour may be processed, data on key bee species reveals that colour is a complex multistage perception largely generated by opponent neural representations in a brain. Thus, a biologically meaningful unit of colour information must consider the psychophysics responses of an animal engaged in colour decision making. We extracted previously collected psychophysics data for a Violet-Sensitive (VS) bird, the pigeon (Columba livia), and used a non-linear function that reliably represents the behavioural choices of hymenopteran and dipteran pollinators to produce the first behaviourally validated and biologically meaningful representation of how VS birds use colour information in a probabilistic way. The function describes how similar or dis-similar spectral information can lead to different choice behaviours in birds, even though all such spectral information is above discrimination threshold. This new representation of bird vision will enable enhanced modelling representations of how bird vision can sense and use colour information in complex environments.

scholarly journals The Limits of Learning: Exploration, Generalization, and the Development of Learning Traps

2018 ◽  
Author(s):  
Alexander Rich ◽  
Todd Matthew Gureckis
Keyword(s):  
Decision Making ◽  
Computer Simulation ◽  
Adaptive Behavior ◽  
False Belief ◽  
Complex Environments ◽  
Extensive Experience ◽  
Present Evidence ◽  
Fundamental Limit ◽  
New Type ◽  
Series Of Experiments

Learning usually improves the accuracy of beliefs through the accumulation of experience. But are there limits to learning that prevent us from accurately understanding our world? In this paper we investigate the concept of a “learning trap”—the formation of a stable false belief even with extensive experience. Our review highlights how these traps develop though the interaction of learning and decision making in unknown environments. We further document a particularly pernicious learning trap driven by selective attention, a mechanism often assumed to facilitate learning in complex environments. Using computer simulation we demonstrate the key attributes of the agent and environment that lead to this new type of learning trap. Then, in a series of experiments we present evidence that people robustly fall into this trap, even in the presence of various interventions predicted to meliorate it. These results highlight a fundamental limit to learning and adaptive behavior that impacts individuals, organizations, animals, and machines.

scholarly journals Uncertainties in complex dynamic environments

2014 ◽  
Vol Volume 2 ◽  
Author(s):  
Hasmik Atoyan ◽  
Jean-Marc Robert ◽  
Jean-Rémi Duquet
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
User Interfaces ◽  
Dynamic Environments ◽  
Decision Making Process ◽  
Uncertain Information ◽  
Complex Environments ◽  
Complex Dynamic ◽  
Different Types ◽  
Machine Systems

The utilization of Decision Support Systems (DSS) in complex dynamic environments leads the human operator almost inevitably to having to face several types of uncertainties. Thus it is essential for system designers to clearly understand the different types of uncertainties that could exist in human-machine systems of complex environments, to know their impacts on the operator's trust in the systems and decision-making process, and to have guidelines on how to present uncertain information on user interfaces. It is also essential for them to have an overview of the different stages, levels, and types of system automation, and to know their possible impacts on the creation of different types of uncertainties. This paper investigates these topics and aim at helping researchers and practitioners to deal with uncertainties in complex environments.

Entrepreneurial fuzzy group decision-making under complex environments

2014 ◽  
Vol 27 (2) ◽  
pp. 901-912 ◽  
Author(s):  
José M. Merigó ◽  
Marta Peris-Ortiz ◽  
Daniel Palacios-Marqués
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Complex Environments ◽  
Fuzzy Group ◽  
Fuzzy Group Decision Making

scholarly journals An obstacle disturbance selection framework: emergent robot steady states under repeated collisions

2020 ◽  
Vol 39 (13) ◽  
pp. 1549-1566
Author(s):  
Feifei Qian ◽  
Daniel E Koditschek
Keyword(s):  
Horizontal Plane ◽  
Robot Dynamics ◽  
Natural Environments ◽  
Complex Environments ◽  
Cluttered Environments ◽  
Robot Trajectory ◽  
Aspect Ratios ◽  
The Face ◽  
Selection Framework ◽  
Contact Position

Natural environments are often filled with obstacles and disturbances. Traditional navigation and planning approaches normally depend on finding a traversable “free space” for robots to avoid unexpected contact or collision. We hypothesize that with a better understanding of the robot–obstacle interactions, these collisions and disturbances can be exploited as opportunities to improve robot locomotion in complex environments. In this article, we propose a novel obstacle disturbance selection (ODS) framework with the aim of allowing robots to actively select disturbances to achieve environment-aided locomotion. Using an empirically characterized relationship between leg–obstacle contact position and robot trajectory deviation, we simplify the representation of the obstacle-filled physical environment to a horizontal-plane disturbance force field. We then treat each robot leg as a “disturbance force selector” for prediction of obstacle-modulated robot dynamics. Combining the two representations provides analytical insights into the effects of gaits on legged traversal in cluttered environments. We illustrate the predictive power of the ODS framework by studying the horizontal-plane dynamics of a quadrupedal robot traversing an array of evenly-spaced cylindrical obstacles with both bounding and trotting gaits. Experiments corroborate numerical simulations that reveal the emergence of a stable equilibrium orientation in the face of repeated obstacle disturbances. The ODS reduction yields closed-form analytical predictions of the equilibrium position for different robot body aspect ratios, gait patterns, and obstacle spacings. We conclude with speculative remarks bearing on the prospects for novel ODS-based gait control schemes for shaping robot navigation in perturbation-rich environments.

The politics of bounded procurement: Purists, brokers and the politics-procurement dichotomy

2014 ◽  
Vol 14 (1) ◽  
pp. 33-61 ◽  
Author(s):  
Alexandru V. Roman
Keyword(s):  
Decision Making ◽  
Public Procurement ◽  
The Body ◽  
The Political ◽  
Original Research ◽  
Complex Environments ◽  
Structured Interviews ◽  
The Future ◽  
Environmental Instability ◽  
The Impact

The last two decades have witnessed a tremendous growth in the body of literature addressing the importance and the impact of contracting and public procurement within the context of devolution of government. The austere budgetary and financial outlooks of the future suggest that the significance of the area will only continue to grow. As such, generating explanatory frameworks, within dimensions such as decisionmaking and accountability in public procurement, becomes crucial. Drawing from original research this article suggests one possible frame for understanding administrative decision-making in complex environments. Based on semi-structured interviews with public procurement specialists, the study identifies two decision-making patterns− broker and purist. It is asserted that the decision-making dynamics exhibited by administrators are contingent on their perceptions regarding environmental instability, in particular the political volatility surrounding their work.

scholarly journals Differential effects of adaptation on odor discrimination

2018 ◽  
Vol 120 (1) ◽  
pp. 171-185 ◽  
Author(s):  
Seth Haney ◽  
Debajit Saha ◽  
Baranidharan Raman ◽  
Maxim Bazhenov
Keyword(s):  
Olfactory Receptor ◽  
Olfactory Receptor Neurons ◽  
Neural Responses ◽  
Complex Environments ◽  
Peripheral Neurons ◽  
Neural Representations ◽  
Complex Stimuli ◽  
Olfactory Systems ◽  
Receptor Neurons ◽  
Distinguishing Features

Adaptation of neural responses is ubiquitous in sensory systems and can potentially facilitate many important computational functions. Here we examined this issue with a well-constrained computational model of the early olfactory circuits. In the insect olfactory system, the responses of olfactory receptor neurons (ORNs) on the antennae adapt over time. We found that strong adaptation of sensory input is important for rapidly detecting a fresher stimulus encountered in the presence of other background cues and for faithfully representing its identity. However, when the overlapping odorants were chemically similar, we found that adaptation could alter the representation of these odorants to emphasize only distinguishing features. This work demonstrates novel roles for peripheral neurons during olfactory processing in complex environments. NEW & NOTEWORTHY Olfactory systems face the problem of distinguishing salient information from a complex olfactory environment. The neural representations of specific odor sources should be consistent regardless of the background. How are olfactory representations robust to varying environmental interference? We show that in locusts the extraction of salient information begins in the periphery. Olfactory receptor neurons adapt in response to odorants. Adaptation can provide a computational mechanism allowing novel odorant components to be highlighted during complex stimuli.

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