Timed automata with observers under energy constraints

2010 ◽  
Author(s):  
Patricia Bouyer ◽  
Uli Fahrenberg ◽  
Kim G. Larsen ◽  
Nicolas Markey
Keyword(s):  
Timed Automata ◽  
Energy Constraints

scholarly journals Infinite Runs in Weighted Timed Automata with Energy Constraints

2008 ◽  
pp. 33-47 ◽  
Author(s):  
Patricia Bouyer ◽  
Uli Fahrenberg ◽  
Kim G. Larsen ◽  
Nicolas Markey ◽  
Jiří Srba
Keyword(s):  
Timed Automata ◽  
Energy Constraints

Modeling and Verifying Services of Internet of Things Based on Timed Automata

2011 ◽  
Vol 34 (8) ◽  
pp. 1365-1377 ◽  
Author(s):  
Li-Xing LI ◽  
Zhi JIN ◽  
Ge LI
Keyword(s):  
Internet Of Things ◽  
Timed Automata

scholarly journals Energy constraints on brain network formation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kosuke Takagi
Keyword(s):  
Network Formation ◽  
Cost Minimization ◽  
Brain Network ◽  
Network Activity ◽  
Rich Functionality ◽  
Energy Constraints ◽  
Dependent Form ◽  
Statistical Similarity ◽  
Simple Ratio ◽  
The Brain

AbstractEnergy constraints are a fundamental limitation of the brain, which is physically embedded in a restricted space. The collective dynamics of neurons through connections enable the brain to achieve rich functionality, but building connections and maintaining activity come at a high cost. The effects of reducing these costs can be found in the characteristic structures of the brain network. Nevertheless, the mechanism by which energy constraints affect the organization and formation of the neuronal network in the brain is unclear. Here, it is shown that a simple model based on cost minimization can reproduce structures characteristic of the brain network. With reference to the behavior of neurons in real brains, the cost function was introduced in an activity-dependent form correlating the activity cost and the wiring cost as a simple ratio. Cost reduction of this ratio resulted in strengthening connections, especially at highly activated nodes, and induced the formation of large clusters. Regarding these network features, statistical similarity was confirmed by comparison to connectome datasets from various real brains. The findings indicate that these networks share an efficient structure maintained with low costs, both for activity and for wiring. These results imply the crucial role of energy constraints in regulating the network activity and structure of the brain.

scholarly journals Priced Timed Automata Models for Control of Intelligent Product Agents in Manufacturing Systems

2020 ◽  
Vol 53 (4) ◽  
pp. 136-142
Author(s):  
Ilya Kovalenko ◽  
Dawn Tilbury ◽  
Kira Barton
Keyword(s):  
Manufacturing Systems ◽  
Timed Automata ◽  
Intelligent Product

scholarly journals Adaptive Cruise Control with Timed Automata

2020 ◽  
Vol 53 (2) ◽  
pp. 1918-1923
Author(s):  
Mustafa Yavuz Kara ◽  
Ebru Aydin Gol
Keyword(s):  
Adaptive Cruise Control ◽  
Timed Automata ◽  
Cruise Control

scholarly journals Configurable verification of timed automata with discrete variables

2020 ◽  
Author(s):  
Tamás Tóth ◽  
István Majzik
Keyword(s):  
Timed Automata ◽  
Empirical Evaluation ◽  
Real Time Systems ◽  
Discrete Variables ◽  
Reachability Problem ◽  
Abstraction Refinement ◽  
Dependent Behavior ◽  
Wide Range ◽  
Time Systems ◽  
Lazy Abstraction

AbstractAlgorithms and protocols with time dependent behavior are often specified formally using timed automata. For practical real-time systems, besides real-valued clock variables, these specifications typically contain discrete data variables with nontrivial data flow. In this paper, we propose a configurable lazy abstraction framework for the location reachability problem of timed automata that potentially contain discrete variables. Moreover, based on our previous work, we uniformly formalize in our framework several abstraction refinement strategies for both clock and discrete variables that can be freely combined, resulting in many distinct algorithm configurations. Besides the proposed refinement strategies, the configurability of the framework allows the integration of existing efficient lazy abstraction algorithms for clock variables based on $${\textit{LU}}$$ LU -bounds. We demonstrate the applicability of the framework and the proposed refinement strategies by an empirical evaluation on a wide range of timed automata models, including ones that contain discrete variables or diagonal constraints.

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