Evolving Training Scenarios with Measurable Variance in Learning Effects

2019 ◽  
pp. 40-51
Author(s):  
Brandt Dargue ◽  
Jeremiah T. Folsom-Kovarik ◽  
John Sanders
Keyword(s):  
Learning Effects

Learning effects on interspecific communication between humans and domestic dogs

2010 ◽  
Author(s):  
Angel M. Elgier ◽  
Adriana Jakovcevic ◽  
Gabriela Barrera ◽  
Alba E. Mustaca ◽  
Mariana Bentosela
Keyword(s):  
Domestic Dogs ◽  
Interspecific Communication ◽  
Learning Effects

Learning Effects and Cell Information Use In Contingency Judgments

1991 ◽  
Author(s):  
Irwin P. Levin ◽  
Shu-Fang Kao ◽  
Edward A. Wasserman
Keyword(s):  
Information Use ◽  
Learning Effects ◽  
Contingency Judgments

Modulation of motivation and attention in perceptual learning: effects upon learning and cortical representation?

2010 ◽  
Vol 41 (01) ◽  
Author(s):  
S Lissek ◽  
O Höffken ◽  
P Stude ◽  
V Nicolas ◽  
H Dinse ◽  
...  
Keyword(s):  
Perceptual Learning ◽  
Cortical Representation ◽  
Learning Effects

scholarly journals Toward a Self-Adaptive Cyberdefense Framework in Organization

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402098885
Author(s):  
Kuan-Jui Huang ◽  
Kuo-Huie Chiang
Keyword(s):  
Information System ◽  
Organizational Learning ◽  
Intelligent Agents ◽  
Coordination Mechanism ◽  
Learning Effects ◽  
Adaptive Model ◽  
Dynamic Propagation ◽  
The Future ◽  
Adaptive Framework ◽  
Self Adaptive

Organizations suffer more than ever from the inability to securely manage the information system, despite their myriad efforts. By introducing a real cyberattack of a bank, this research analyzes the characteristics of modern cyberattacks and simulates the dynamic propagation that makes them difficult to manage. It develops a self-adaptive framework that through simulation, distinctly improves cyberdefense efficiency. The results illustrate the discrepancies of the previous studies and validate the use of a time-based self-adaptive model for cybersecurity management. The results further show the significance of human and organizational learning effects and a coordination mechanism in obtaining a highly dependable cyberdefense setting. This study also provides an illuminating analysis for humans to position themselves in the collaborations with increasingly intelligent agents in the future.

Bicriterion scheduling with truncated learning effects and convex controllable processing times

2020 ◽  
Vol 28 (3) ◽  
pp. 1573-1593
Author(s):  
Ji‐Bo Wang ◽  
Dan‐Yang Lv ◽  
Jian Xu ◽  
Ping Ji ◽  
Fuqiang Li
Keyword(s):  
Controllable Processing Times ◽  
Learning Effects ◽  
Processing Times
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