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https://doi.org/10.1109/wodes....
Article . 2008 . Peer-reviewed
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Discreteness, hybrid automata, and biology

Authors: CASAGRANDE, A; PIAZZA, Carla; POLICRITI, Alberto;

Discreteness, hybrid automata, and biology

Abstract

Most of the observable natural phenomena exhibit a mixed discrete-continuous behavior characterized by laws changing according to a phase cycle. Such behaviors can be modeled in a very natural way by a class of automata called hybrid automata. In this class the evolution of measurable quantities, such as concentrations, is represented according to both dynamical system evolutions - on dense domains - and rules phases through a discrete transition structure. Once the real systems are modeled in such a framework, one may want to analyze them by applying automatic techniques, such as model checking or abstract interpretation. Unfortunately, the interleaving of dense and discrete evolutions soon leads to undecidability results on hybrid automata. This paper addresses questions regarding the decidability of reachability problem for hybrid automata (i.e., "Can the systems reach a state a from a state b?") by proposing a more "Nature"-oriented semantics. In particular, after observing that dense domains are abstractions of real world, we suggest that, for any biological system, there should be a value epsilon such that if the distance of two objects are less than epsilon, we cannot distinguish them. Using the above considerations, we propose a new semantics for hybrid automata which guarantees the decidability of reachability. Moreover, we provide a biological example showing that the new semantics mimics the real world behaviors better than the "classical" one.

Country
Italy
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Keywords

Approximate Semantic, First-Order Logic, Hybrid Automata; Approximate Semantics; First-Order Logics; Decidability; Biology, Decidability, Hybrid Automata, Biology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Top 10%
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