Multiple-Process Models for Perception-Action Systems

1994 ◽  
Author(s):  
James T. Townsend ◽  
Thomas G. Fikes
Keyword(s):  
Process Models ◽  
Action Systems ◽  
Multiple Process ◽  
Perception Action

Validating Component-Based Implementations of Business Processes

2011 ◽  
pp. 124-151
Author(s):  
Jens Lemcke ◽  
Andreas Friesen ◽  
Tirdad Rahmani
Keyword(s):  
Petri Nets ◽  
Business Process ◽  
Business Processes ◽  
Process Models ◽  
Action Refinement ◽  
Deadlock Analysis ◽  
Multiple Process ◽  
Component Based Software Engineering ◽  
Exponential Complexity ◽  
Different Levels

This chapter provides a formal specification of non-atomic, relaxed action refinement suited for component-based business process engineering. Engineering a business process involves multiple process models created by different people on different levels of abstractions. Keeping the models consistent during the engineering procedure—refinement validation—is one objective of this chapter. In component-based software engineering, the lowest abstraction of a business process is mapped on existing components that have a description of their behaviors. Checking the consistency of process and component behavior—grounding validation—is the second objective. Both refinement and grounding validation increase the robustness of business process implementations and the productivity of process engineers. Technically, the specification given in this chapter is in terms of deadlock analysis in safe Petri nets. The evaluation of this straight-forward implementation underlines the exponential complexity of deadlock analysis in safe Petri nets. For use cases with more than 30 activities per process or heavy parallelism, optimized implementations are needed.

A Generic Model for Perception-Action Systems. Analysis of a Knowledge-Based Prototype

1999 ◽  
pp. 293-311
Author(s):  
D. Hernández-Sosa ◽  
J. Lorenzo-Navarro ◽  
M. Hernández-Tejera ◽  
J. Cabrera-Gámez ◽  
A. Falcón-Martel ◽  
...  
Keyword(s):  
Systems Analysis ◽  
Generic Model ◽  
Action Systems ◽  
Knowledge Based ◽  
Perception Action

Adapting Perception, Action, and Technology for Mathematical Reasoning

2017 ◽  
Vol 26 (5) ◽  
pp. 434-441 ◽  
Author(s):  
Robert L. Goldstone ◽  
Tyler Marghetis ◽  
Erik Weitnauer ◽  
Erin R. Ottmar ◽  
David Landy
Keyword(s):  
Perception And Action ◽  
Mathematical Reasoning ◽  
Cognitive Tasks ◽  
Algebraic Reasoning ◽  
Test Case ◽  
Action Systems ◽  
Computer Based ◽  
Formal Requirements ◽  
Cultural Tools ◽  
Perception Action

Formal mathematical reasoning provides an illuminating test case for understanding how humans can think about things that they did not evolve to comprehend. People engage in algebraic reasoning by (1) creating new assemblies of perception and action routines that evolved originally for other purposes (reuse), (2) adapting those routines to better fit the formal requirements of mathematics (adaptation), and (3) designing cultural tools that mesh well with our perception-action routines to create cognitive systems capable of mathematical reasoning (invention). We describe evidence that a major component of proficiency at algebraic reasoning is Rigged Up Perception-Action Systems (RUPAS), via which originally demanding, strategically controlled cognitive tasks are converted into learned, automatically executed perception and action routines. Informed by RUPAS, we have designed, implemented, and partially assessed a computer-based algebra tutoring system called Graspable Math with an aim toward training learners to develop perception-action routines that are intuitive, efficient, and mathematically valid.

Motor cognition: TMS studies of action generation

2012 ◽  
Author(s):  
Simone Schütz-Bosbach ◽  
Patrick Haggard ◽  
Luciano Fadiga ◽  
Laila Craighero
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Magnetic Stimulation ◽  
Cortical Excitability ◽  
Motor Cognition ◽  
Action Systems ◽  
Motor Processes ◽  
Cortical Motor ◽  
Motor Excitability ◽  
Perception Action ◽  
Second Use

Transcranial magnetic stimulation (TMS) has been used to study motor configuration in three ways. TMS can be used to provide a controllable and physiologically specified input to the skeletomotor system. Second, use of TMS has been as an online probe of cortical motor excitability. Third, TMS can be used to interfere with cognitive-motor processes involved in action control. TMS allows the experimenter to selectively interfere with a specific brain process. TMS has proved a valuable tool for testing parallel models of perception–action linkage, because it can be used to measure cortical excitability. TMS has been used as both an excitability measure and a transient inactivation. TMS has allowed neuroscientists to activate or inactivate the brain's action systems artificially. This has provided key insights into normal motor function.

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