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Inferring Executable Models from Formalized Experimental Evidence [chapter]

Vivek Nigam, Robin Donaldson, Merrill Knapp, Tim McCarthy, Carolyn Talcott
2015 Lecture Notes in Computer Science  
As a first step in addressing this problem, this paper introduces an automated method for deriving executable models from formalized experimental findings called datums.  ...  However, the process of building an executable model from published experimental findings is still carried out manually. The process is very time consuming and requires expert knowledge.  ...  The problem of automatically constructing executable models from experimental evidence has several aspects including: (1) formal representation of experimental findings, (2) formal representation of  ... 
doi:10.1007/978-3-319-23401-4_9 fatcat:a3rtbddetbbo7laplf3hzffvwi

Towards Inverse Uncertainty Quantification in Software Development (Short Paper) [chapter]

Matteo Camilli, Angelo Gargantini, Patrizia Scandurra, Carlo Bellettini
2017 Lecture Notes in Computer Science  
) and the formal specification (i.e., a mathematical model) of the system under consideration, and the value calibration of unknown parameters in the model.  ...  purpose of delivering more robust systems, this paper revisits the problem of Inverse Uncertainty Quantification that is related to the discrepancy between the measured data at runtime (while the system executes  ...  ), algorithmic uncertainty (coming from numerical approximations per implementation of the computer model), experimental uncertainty (due to the inherent variability of experimental measurements), etc.  ... 
doi:10.1007/978-3-319-66197-1_24 fatcat:rqb5pxterbagtlpcgwz6v3mray

Automatic Test Set Generation for Event-Driven Systems in the Absence of Specifications Combining Testing with Model Inference

Luigi Novella, Manuela Tufo, Giovanni Fiengo
2019 Information Technology and Control  
It basically involves active learning to automatically infer a behavioural model of the System Under Test (SUT) using tests as queries, generates further tests based on the learned model to systematically  ...  Our passive learning algorithm uses the basic steps of Evidence-Driven State Merging (EDSM) and introduces an effective heuristic for choosing the pair of states to merge to obtain the target machine.  ...  The inferred model is then the result of what we learn from test execution, therefore it provides a functional perspective on the test set.  ... 
doi:10.5755/j01.itc.48.2.21725 fatcat:ctyej5v7ifa7pjtmz333xktjo4

Dichotomies between computational and mathematical models

C Anthony Hunt, Glen E P Ropella, Sunwoo Park, Jesse Engelberg
2008 Nature Biotechnology  
Both model types must be translated from the formalism into machine code.  ...  "Because computational models are qualitative, they do not presuppose a precision absent from the experimental data; because they are nondeterministic or stochastic, they allow many possible outcomes of  ...  First, one cannot directly compare an executing model to data. One must take measurements from the executing model just as one does during execution of a wet-lab, experimental model.  ... 
doi:10.1038/nbt0708-737 pmid:18612289 fatcat:6ef6jxrcmje2zpdrctbndttmgm


2007 Worldviews, Science and Us  
Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest.  ...  The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences.  ...  The process of executing a program in a computer can be formally modelled, and thus understood as an automatic process of formal inference.  ... 
doi:10.1142/9789812707420_0017 fatcat:bg6tg7xaejfibhabkauqwssede

A constraint-based approach for proactive, context-aware human support

Federico Pecora, Marcello Cirillo, Francesca Dell'Osa, Jonas Ullberg, Alessandro Saffiotti
2012 Journal of Ambient Intelligence and Smart Environments  
Pecora et al. (2012) provide a formal and experimental validation of SAM.  ...  The domain description formalism used by SAM is based on metric temporal constraints; such domains model both the criteria for context inference and the planning operators used for plan synthesis.  ... 
doi:10.3233/ais-2012-0157 fatcat:bzse2n7savgzpajvkbrifpnevi

Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast

Anthony Coutant, Katherine Roper, Daniel Trejo-Banos, Dominique Bouthinon, Martin Carpenter, Jacek Grzebyta, Guillaume Santini, Henry Soldano, Mohamed Elati, Jan Ramon, Celine Rouveirol, Larisa N. Soldatova (+1 others)
2019 Proceedings of the National Academy of Sciences of the United States of America  
All of the experiments were formalized and communicated to a cloud laboratory automation system (Eve) for automatic execution, and the results stored on the semantic web for reuse.  ...  We combined multiple software tools with integrated laboratory robotics to execute three cycles of model improvement of the prototypical eukaryotic cellular transformation, the yeast (Saccharomyces cerevisiae  ...  We received support from the CHIST-ERA AdaLab project: The Engineering and Physical Sciences Research Council (EPSRC), UK (EP/M015661/1), ANR-14-CHR2-0001-01.  ... 
doi:10.1073/pnas.1900548116 pmid:31420515 pmcid:PMC6731661 fatcat:x4wq2gbpdvanlmz4ud75jjjeg4


2005 Modeling Language, Cognition and Action  
These constraints include recent experimental evidence that details of neural computation and brain architecture play a crucial role in language processing.  ...  The Neural Theory of Language project aims to build structured connectionist models of language and cognition consistent with constraints from all domains and at all levels.  ...  This basic model is extended so that simulation-based inferences in the source domain (e.g., resulting from executing a FALL x-schema) are projected via metaphorical mappings (e.g., FALLING IS FAILURE)  ... 
doi:10.1142/9789812701886_0005 fatcat:vegudmzdfrekra6drhdz2xucfu

Modeling social inference in virtual agents

Wenji Mao, Jonathan Gratch
2009 AI & Society: The Journal of Human-Centred Systems and Machine Intelligence  
Such inferences are a key aspect of social intelligence that underlie social planning, social learning, natural language pragmatics and computational models of emotion.  ...  of social inference.  ...  Causal inference derives beliefs from causal evidence. Dialogue inference derives beliefs from communicative acts.  ... 
doi:10.1007/s00146-009-0195-4 fatcat:bdgovf4grfhmda4xgbndgjayx4

Forthcoming papers

1998 Artificial Intelligence  
Indeed, it inherits formal and practical tools from the area of Concurrency in Computer Science, to deal with complex actions, treating suitably aspects like nonterminating executions, parallelism, communications  ...  The effectiveness of this approach is demonstrated analytically, and experimentally. N.M.  ...  Indeed, it inherits formal and practical tools from the area of Concurrency in Computer Science, to deal with complex actions, treating suitably aspects like nonterminating executions, parallelism, communications  ... 
doi:10.1016/s0004-3702(98)90017-0 fatcat:64e2tieswrephofjnwmo2wh3ga

Page 29 of Journal of Systems Management Vol. 20, Issue 5 [page]

1969 Journal of Systems Management  
Once the model has been formu- MAY e 1969 lated, formal inference is used to formulate new, deriva- tive, judgments.  ...  In other words, the correct use of the formal process of inference does not guard against erroneous results.  ... 

The mirror-neuron system: a Bayesian perspective

James M. Kilner, Karl J. Friston, Chris D. Frith
2007 NeuroReport  
es a precise role for the mirror-neuron system in our ability to infer intentions from observed movement and outlines possible computational mechanisms.  ...  Precisely how intentions can be inferred through movement-observation, however, has provoked much debate.  ...  It can be shown that this scheme is formally equivalent to empirical Bayesian inference, in which prior expectations emerge naturally from the hierarchal models employed [14, 15] .  ... 
doi:10.1097/wnr.0b013e3281139ed0 pmid:17413668 fatcat:gwgzxuvbovfxdngryqd6j6shce

Inferring Markov Chain for Modeling Order Book Dynamics in High Frequency Environment

Yuan Lung Chang
2015 International Journal of Machine Learning and Computing  
In this paper, we propose a Bayesian inference of the Markov chain model class to model dynamics of order book in high frequency trading environment.  ...  Experimental result based on security AAPL showed over 98% coverage by 50 transitions from 6561 state space. It further indicated market behavior of short time-frame can be clustered & labeled.  ...  A limit order from the order book can be executed or canceled.  ... 
doi:10.7763/ijmlc.2015.v5.515 fatcat:ip6cefsijzhi3bus6h6i6ly34m

Gene Ontology annotations: what they mean and where they come from

David P Hill, Barry Smith, Monica S McAndrews-Hill, Judith A Blake
2008 BMC Bioinformatics  
scientists. from 10 th Bio-Ontologies Special Interest Group Workshop 2007.  ...  are captured in annotations, in the hope that this will lead both to better representations of biological reality through annotation and ontology development and to more informed use of GO resources by experimental  ...  For example, the evidence code IDA (Inferred from Direct Assay) is used when an experimenter has devised an assay that measures the execution of a given molecular function and the experimental results  ... 
doi:10.1186/1471-2105-9-s5-s2 pmid:18460184 pmcid:PMC2367625 fatcat:kyqh4usdu5akfmsygvvrlcdkri

Modeling Design Patterns with Description Logics: A Case Study [chapter]

Yudistira Asnar, Elda Paja, John Mylopoulos
2011 Lecture Notes in Computer Science  
To evaluate the scalability of our approach, we present experimental results using models inspired by an industrial case study.  ...  In this work, we propose to formalize such patterns in a formal modeling language, thereby automating pattern matching for a given problem.  ...  Acknowledgments The research leading to these results has received funding from the EU FP7 under grants no. 216917 MASTER, no. 256980 NESSoS, and no. 257930 ANIKETOS.  ... 
doi:10.1007/978-3-642-21640-4_14 fatcat:b2zkigk2pfdcbgqkdbx4jd4ede
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