Launch : Model Based Systems Model of NASA Launch Vehicles

2016 ◽  
Author(s):  
Chrishma H. Singh-derewa ◽  
Priyanka Srivastava
Keyword(s):  
Launch Vehicles ◽  
Model Based ◽  
Systems Model

Model-Based and Model-Free Social Cognition

2019 ◽  
Author(s):  
Leor M Hackel ◽  
Jeffrey Jordan Berg ◽  
Björn Lindström ◽  
David Amodio
Keyword(s):  
Reinforcement Learning ◽  
Social Cognition ◽  
Learning Strategies ◽  
Memory Systems ◽  
Learning Task ◽  
Financial Advisors ◽  
Model Based ◽  
Model Free ◽  
Systems Model ◽  
Task Assessment

Do habits play a role in our social impressions? To investigate the contribution of habits to the formation of social attitudes, we examined the roles of model-free and model-based reinforcement learning in social interactions—computations linked in past work to habit and planning, respectively. Participants in this study learned about novel individuals in a sequential reinforcement learning paradigm, choosing financial advisors who led them to high- or low-paying stocks. Results indicated that participants relied on both model-based and model-free learning, such that each independently predicted choice during the learning task and self-reported liking in a post-task assessment. Specifically, participants liked advisors who could provide large future rewards as well as advisors who had provided them with large rewards in the past. Moreover, participants varied in their use of model-based and model-free learning strategies, and this individual difference influenced the way in which learning related to self-reported attitudes: among participants who relied more on model-free learning, model-free social learning related more to post-task attitudes. We discuss implications for attitudes, trait impressions, and social behavior, as well as the role of habits in a memory systems model of social cognition.

Neuman Systems Model-Based Research: An Integrative Review Project

2001 ◽  
Vol 14 (3) ◽  
pp. 231-238
Author(s):  
Jacqueline Fawcett ◽  
Sandra K. Giangrande
Keyword(s):  
Integrative Review ◽  
Model Based ◽  
Neuman Systems Model ◽  
Systems Model ◽  
Neuman Systems

A Systems Model of Communication Processes

1978 ◽  
Vol 8 (4) ◽  
pp. 321-342 ◽  
Author(s):  
C. G. Bruckmann
Keyword(s):  
Communication System ◽  
System Approach ◽  
Communication Studies ◽  
Transfer System ◽  
Human Communication ◽  
Human System ◽  
Model Based ◽  
Systems Model ◽  
Communication Processes ◽  
Commerce Students

In the teaching of communication studies to engineering and commerce students, the time available for teaching communication principles and models did not allow for a detailed study of the various models currently in use. A systems model based on a consistent and limited terminology was developed. This model consists essentially of three subsystems; the human system, the message transfer system, and intermediate receiver-storage-transmitter systems. With the use of this system approach, it is possible to construct models of any human communication system and to use these models to analyze and compare the strengths and weaknesses of the different systems.

scholarly journals Testing Asynchronous Reactive Systems: Beyond the ioco framework

2021 ◽  
Vol 24 (2) ◽  
Author(s):  
Adilson Bonifacio ◽  
Arnaldo Vieira Moura
Keyword(s):  
Reactive Systems ◽  
Model Based ◽  
Systems Model ◽  
Model Based Testing ◽  
Special Cases ◽  
Implementation Under Test ◽  
Complete Test ◽  
Manual Testing ◽  
Special Case ◽  
Test Suites

Manual testing can be rather time consuming and prone to errors specially when testing asynchronous reactive systems. Model based testing is a well-established approach to verify reactive systems specified by input output labeled transition systems (IOLTSs). One of the challenges stemming from model based testing is verifying conformance and, also, generating test suites, primarily when completeness is a required property. In order to check whether an implementation under test is in compliance with its respective specification one resorts to some form of conformance relation that guarantees the expected behavior of the implementations, given the behavior of the specification. The ioco relation is an example of such a conformance relation. In this work we study another conformance relation based on formal languages. We also investigate how to generate finite and complete test suites for IOLTS models, and discuss the complexity of the test generation mechanism under this new conformance relation. We also show that ioco is a special case of this new conformance relation. Further, we relate our contributions to more recent works, accommodating the restrictions of their classes of fault models as special cases, and we expose the complexity of generating any complete test suite that must satisfy their restrictions.

Sign in / Sign up

Export Citation Format

Share Document