Transforming organizational culture in complex, dynamic environments for safety

2009 ◽  
Author(s):  
Sallie J. Weaver ◽  
Rebecca Lyons ◽  
Eduardo Salas ◽  
David A. Hofmann
2014 ◽  
Vol Volume 2 ◽  
Author(s):  
Hasmik Atoyan ◽  
Jean-Marc Robert ◽  
Jean-Rémi Duquet

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.


Neuron ◽  
2011 ◽  
Vol 69 (5) ◽  
pp. 1015-1028 ◽  
Author(s):  
Davide Nardo ◽  
Valerio Santangelo ◽  
Emiliano Macaluso

2020 ◽  
Vol 117 (23) ◽  
pp. 12693-12699 ◽  
Author(s):  
Vedant Sachdeva ◽  
Kabir Husain ◽  
Jiming Sheng ◽  
Shenshen Wang ◽  
Arvind Murugan

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.


1992 ◽  
Vol 01 (03n04) ◽  
pp. 411-449 ◽  
Author(s):  
LEE SPECTOR ◽  
JAMES HENDLER

For intelligent systems to interact with external agents and changing domains, they must be able to perceive and to affect their environments while computing long term projection (planning) of future states. This paper describes and demonstrates the supervenience architecture, a multilevel architecture for integrating planning and reacting in complex, dynamic environments. We briefly review the underlying concept of supervenience, a form of abstraction with affinities both to abstraction in AI planning systems, and to knowledge-partitioning schemes in hierarchical control systems. We show how this concept can be distilled into a strong constraint on the design of dynamic-world planning systems. We then describe the supervenience architecture and an implementation of the architecture called APE (for Abstraction-Partitioned Evaluator). The application of APE to the HomeBot domain is used to demonstrate the capabilities of the architecture.


2015 ◽  
Vol 12 (03) ◽  
pp. 1550024 ◽  
Author(s):  
Daniel H. García ◽  
Concepción A. Monje ◽  
Carlos Balaguer

Humanoid robots are required to perform a wide repertoire of tasks working beside humans in complex dynamic environments. Learning mechanisms are important for building up these types of repertoires of robot skills. However, despite the clear advantages of these approaches, it would be impractical to teach the robot skills for every needed task and for every foreseen situation. Robot skills learning approaches to develop humanoid robotic systems would have greater impact if the models of the skills can be operated upon to generate new behaviors of increasing levels of complexity. A framework that allows the adaptation of previously learned motion skills to new unseen contexts is necessary. In this work, we present different modalities for the adaptation and generation of new skill models based on the already learned models of the skills. Experimental results are presented to validate this approach.


2019 ◽  
Vol 18 (4) ◽  
pp. 470-506 ◽  
Author(s):  
Fotios Mitsakis

This integrative literature review reports on strategic human resource development (SHRD) models that examine the strategic embeddedness of HRD (SHRD maturity) in organizations. A review and critique of all existing SHRD models is provided, exemplifying their limitations and building upon their strengths to inform a modified SHRD framework. The latter suggests an enhanced set of strategic components to assess SHRD maturity. This article further outlines how SHRD aspirations can be practiced within complex, dynamic, and continually changing business and economic environments. The SHRD literature is advanced by new insights on how HRD scholars and practitioners could assess and enhance the maturity of their HRD interventions in the context of constantly changing (dynamic) environments. The modified SHRD framework further contributes to the academic literature with its enhanced set of strategic characteristics, as well as with its SHRD pointers, all of which can offer a better evaluation of SHRD maturity during periods of business and economic complexity and uncertainty.


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