This paper presents a framework of how to apply compositional and assume-guarantee reasoning to linear time-invariant (LTI) systems.
Compositional analysis techniques such as assume-guarantee reasoning are frequently used in computer science to validate the design of complex process models.
At the end of the paper, we discussed the verification problem, and its decomposition to sub-problems with lower complexity as the consequence of the compositional semantics and component refinement using the rules of assume-guarantee reasoning.
While results with regard to compositional analysis have been presented for discrete and recently also for continuous-time systems, it is our aim to develop compositional and assume-guarantee reasoning for a specific class of hybrid systems, namely switching linear systems.
In addition to using the specificity of the model for tailoring the verification algorithm, methods used in software and hardware modification, such as assume-guarantee reasoning [ 44], or Counterexample-guided Abstraction Refinement [ 45] could also be applied to models of biological systems.
We then give sufficiency conditions for particular knowledge representation formalisms that guarantee that abductive reasoning can indeed be done through filtering and present examples from the knowledge representation literature where abductive reasoning is done through filtering.
If the answer to both questions is Yes, then the argument creates a presumption for the conclusion but not a guarantee, for the reasoning is defeasible: other information may come to light that will override the presumption.
Guaranteed Apple's reasoning behind a Beats purchase goes a lot deeper than 'we have all these billions burning a hole in our pocket,' but it's funny to see the armchair analyst crowd's opinion so neatly summed up.
Taking into account (8), a well-known reasoning guarantees that there exist ε 0 > 0 and two partial subsequences { g x m ( k ) } and { g x n ( k ) } such that k ≤ m ( k ) < n ( k ), d ( g x m ( k ), g x n ( k ) − 1 ) ≤ ε 0 < d ( g x m ( k ), g x n ( k ) ) for all k, (9).
5. Deduction: ability to refine the truth of a conclusion; for example, the correct nursing diagnosis is guaranteed by the reasoning.
Meanwhile, the multichains reasoning algorithm guarantees that reasoner can perform multiple reasoning tasks defined by users themselves in a MapReduce job.
