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Author Tronci, Enrico
Title (down) Optimal Finite State Supervisory Control Type Conference Article
Year 1996 Publication CDC '96: Proceedings of the 35th IEEE International Conference on Decision and Control Abbreviated Journal
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Abstract Supervisory Controllers are Discrete Event Dynamic Systems (DEDSs) forming the discrete core of a Hybrid Control System. We address the problem of automatic synthesis of Optimal Finite State Supervisory Controllers (OSCs). We show that Boolean First Order Logic (BFOL) and Binary Decision Diagrams (BDDs) are an effective methodological and practical framework for Optimal Finite State Supervisory Control. Using BFOL programs (i.e. systems of boolean functional equations) and BDDs we give a symbolic (i.e. BDD based) algorithm for automatic synthesis of OSCs. Our OSC synthesis algorithm can handle arbitrary sets of final states as well as plant transition relations containing loops and uncontrollable events (e.g. failures). We report on experimental results on the use of our OSC synthesis algorithm to synthesize a C program implementing a minimum fuel OSC for two autonomous vehicles moving on a 4 x 4 grid.
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Publisher IEEE Computer Society Place of Publication Washington, DC, USA Editor
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Notes Approved yes
Call Number Sapienza @ mari @ cdc96 Serial 67
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Author Mancini, T.; Tronci, E.; Scialanca, A.; Lanciotti, F.; Finzi, A.; Guarneri, R.; Di Pompeo, S.
Title (down) Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network Type Conference Article
Year 2018 Publication 25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018) Abbreviated Journal
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Notes Approved no
Call Number MCLab @ davi @ Serial 174
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Author Alimguzhin, Vadim; Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico
Title (down) On-the-Fly Control Software Synthesis Type Conference Article
Year 2013 Publication Proceedings of International SPIN Symposium on Model Checking of Software (SPIN 2013) Abbreviated Journal International SPIN Symposium on Model Checking of Software
Volume Issue Pages 61-80
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Publisher Springer - Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title
Series Volume 7976 Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-39175-0 Medium
Area Expedition Conference
Notes Approved yes
Call Number Sapienza @ melatti @ Serial 111
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Author Bartolini, Novella; Tronci, Enrico
Title (down) On Optimizing Service Availability of an Internet Based Architecture for Infrastructure Protection Type Conference Article
Year 2006 Publication Cnip Abbreviated Journal
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Call Number Sapienza @ mari @ Bt06 Serial 28
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Author Alimguzhin, Vadim; Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico
Title (down) On Model Based Synthesis of Embedded Control Software Type Conference Article
Year 2012 Publication Proceedings of the 12th International Conference on Embedded Software, EMSOFT 2012, part of the Eighth Embedded Systems Week, ESWeek 2012, Tampere, Finland, October 7-12, 2012 Abbreviated Journal
Volume Issue Pages 227-236
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Publisher ACM Place of Publication Editor Ahmed Jerraya and Luca P. Carloni and Florence Maraninchi and John Regehr
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Series Editor Series Title Abbreviated Series Title
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ISSN ISBN 978-1-4503-1425-1 Medium
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Notes Techreport version can be found at arxiv.org Approved yes
Call Number Sapienza @ mari @ emsoft12 Serial 97
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Author Alimguzhin, Vadim; Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico
Title (down) On Model Based Synthesis of Embedded Control Software Type Report
Year 2012 Publication Abbreviated Journal
Volume abs/1207.4474 Issue Pages
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Abstract Many Embedded Systems are indeed Software Based Control Systems (SBCSs), that is control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for control software. Given the formal model of a plant as a Discrete Time Linear Hybrid System and the implementation specifications (that is, number of bits in the Analog-to-Digital (AD) conversion) correct-by-construction control software can be automatically generated from System Level Formal Specifications of the closed loop system (that is, safety and liveness requirements), by computing a suitable finite abstraction of the plant.
With respect to given implementation specifications, the automatically generated code implements a time optimal control strategy (in terms of set-up time), has a Worst Case Execution Time linear in the number of AD bits $b$, but unfortunately, its size grows exponentially with respect to $b$. In many embedded systems, there are severe restrictions on the computational resources (such as memory or computational power) available to microcontroller devices.
This paper addresses model based synthesis of control software by trading system level non-functional requirements (such us optimal set-up time, ripple) with software non-functional requirements (its footprint). Our experimental results show the effectiveness of our approach: for the inverted pendulum benchmark, by using a quantization schema with 12 bits, the size of the small controller is less than 6% of the size of the time optimal one.
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Publisher CoRR, Technical Report Place of Publication Editor
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Notes Approved yes
Call Number Sapienza @ mari @ Serial 102
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Author Mancini, T. ; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Tronci, E.
Title (down) On minimising the maximum expected verification time Type Journal Article
Year 2017 Publication Information Processing Letters Abbreviated Journal
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Notes Approved no
Call Number Sapienza @ mari @ Serial 163
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Author Tronci, Enrico
Title (down) On Computing Optimal Controllers for Finite State Systems Type Conference Article
Year 1997 Publication CDC '97: Proceedings of the 36th IEEE International Conference on Decision and Control Abbreviated Journal
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Publisher IEEE Computer Society Place of Publication Washington, DC, USA Editor
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Notes Approved yes
Call Number Sapienza @ mari @ cdc97 Serial 66
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Author Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Tronci, E.
Title (down) On Checking Equivalence of Simulation Scripts Type Journal Article
Year 2021 Publication Journal of Logical and Algebraic Methods in Programming Abbreviated Journal
Volume Issue Pages 100640
Keywords Formal verification, Simulation based formal verification, Formal Verification of cyber-physical systems, System-level formal verification
Abstract To support Model Based Design of Cyber-Physical Systems (CPSs) many simulation based approaches to System Level Formal Verification (SLFV) have been devised. Basically, these are Bounded Model Checking approaches (since simulation horizon is of course bounded) relying on simulators to compute the system dynamics and thereby verify the given system properties. The main obstacle to simulation based SLFV is the large number of simulation scenarios to be considered and thus the huge amount of simulation time needed to complete the verification task. To save on computation time, simulation based SLFV approaches exploit the capability of simulators to save and restore simulation states. Essentially, such a time saving is obtained by optimising the simulation script defining the simulation activity needed to carry out the verification task. Although such approaches aim to (bounded) formal verification, as a matter of fact, the proof of correctness of the methods to optimise simulation scripts basically relies on an intuitive semantics for simulation scripting languages. This hampers the possibility of formally showing that the optimisations introduced to speed up the simulation activity do not actually omit checking of relevant behaviours for the system under verification. The aim of this paper is to fill the above gap by presenting an operational semantics for simulation scripting languages and by proving soundness and completeness properties for it. This, in turn, enables formal proofs of equivalence between unoptimised and optimised simulation scripts.
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ISSN 2352-2208 ISBN Medium
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Notes Approved no
Call Number MCLab @ davi @ Mancini2021100640 Serial 183
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Author Tortora, L.; Meynen, G.; Bijlsma, J.; Tronci, E.; Ferracuti, S.
Title (down) Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective Type Journal Article
Year 2020 Publication Frontiers in Psychology Abbreviated Journal
Volume 11 Issue Pages 220
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Abstract Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as ‘A.I. neuroprediction,’ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed.
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ISSN 1664-1078 ISBN Medium
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Notes Approved no
Call Number MCLab @ davi @ Neuroprediction-2020 Serial 180
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