1,721,092 research outputs found
Scientific theories of computational systems in model checking
Model checking, a prominent formal method used to predict and explain the behaviour of software and hardware systems, is examined on the basis of reflective work in the philosophy of science concerning the ontology of scientific theories and model-based reasoning. The empirical theories of computational systems that model checking techniques enable one to build are identified, in the light of the semantic conception of scientific theories, with families of models that are interconnected by simulation relations. And the mappings between these scientific theories and computational systems in their scope are analyzed in terms of suitable specializations of the notions of model of experiment and model of data. Furthermore, the extensively mechanized character of model-based reasoning in model checking is highlighted by a comparison with proof procedures adopted by other formal methods in computer science. Finally, potential epistemic benefits flowing from the application of model checking in other areas of scientific inquiry are emphasized in the context of computer simulation studies of biological information processing
Scientific Theories of Computational Systems in Model Checking
Model checking, a prominent formal method used to predict and explain the behaviour of software and hardware systems, is examined on the basis of reflective work in the philosophy of science concerning the ontology of scientific theories and model-based reasoning. The empirical theories of computational systems that model checking techniques enable one to build are identified, in the light of the semantic conception of scientific theories, with families of models that are interconnected by simulation relations. And the mappings between these scientific theories and computational systems in their scope are analyzed in terms of suitable specializations of the notions of model of experiment and model of data. Furthermore, the extensively mechanized character of model-based reasoning in model checking is highlighted by a comparison with proof procedures adopted by other formal methods in computer science. Finally, potential epistemic benefits flowing from the application of model checking in other areas of scientific inquiry are emphasized in the context of computer simulation studies of biological information processing
Neuromodulation and neural circuit performativity: Adequacy conditions for their computational modelling
An understanding of the functional repertoire of neural circuits and their plasticity requires knowledge of neural connectivity diagrams and their dynamical evolution. However, one must additionally take into account the fast and reversible functional effects induced by neuromodulatory mechanisms which do not alter neural circuit diagrams. Neuromodulators contribute crucially to determine the performativity of a neural circuit, that is, its ability to change behavior, and especially behavioral changes occurring under temporal constraints that are incompatible with the longer time scales of Hebbian learning and other forms of neural learning. This paper focuses on two properties of neuromodulatory action that have been relatively neglected so far. These properties are the functional soundness of neuromodulated circuits and the robustness of neuromodulatory action. Both properties are analyzed here as sources of functional specifications for the computational modeling of neural circuit performativity. In particular, taking dynamical systems that are based on CTRNNs (Continuous Time Recurrent Neural Networks) as an exemplary class of computational models, it is argued that robustness is suitably modeled there by means of a hysteresis process, and functional soundness by means of a multiplicity of stable fixed points
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