Colin Paterson

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 41

Top Topics

Business Processes

Autonomous Systems

Top Venues

Publications

Xinwei Fang, Sinem Getir Yaman, Radu Calinescu, Julie Wilson, Colin Paterson
Predicting Nonfunctional Requirement Violations in Autonomous Systems. ACM Trans. Auton. Adapt. Syst. 19 (1) (2024)
Calum Imrie, Rhys Howard, Divya Thuremella, Nawshin Mannan Proma, Tejas Pandey, Paulina Lewinska, Ricardo Cannizzaro, Richard Hawkins, Colin Paterson, Lars Kunze, Victoria J. Hodge
Aloft: Self-Adaptive Drone Controller Testbed. SEAMS@ICSE (2024)
Ozan Vardal, Richard Hawkins, Colin Paterson, Chiara Picardi, Daniel Omeiza, Lars Kunze, Ibrahim Habli
Learning Run-time Safety Monitors for Machine Learning Components. CoRR (2024)
John A. McDermid, Radu Calinescu, Ibrahim Habli, Richard Hawkins, Yan Jia, John Molloy, Matt Osborne, Colin Paterson, Zoë Porter, Philippa Ryan Conmy
The Safety of Autonomy: A Systematic Approach. Computer 57 (4) (2024)
Chiara Picardi, Richard Hawkins, Colin Paterson, Ibrahim Habli
Transfer Assurance for Machine Learning in Autonomous Systems. SafeAI@AAAI (2023)
Sinem Getir Yaman, Ana Cavalcanti, Radu Calinescu, Colin Paterson, Pedro Ribeiro, Beverley Townsend
Specification, Validation and Verification of Social, Legal, Ethical, Empathetic and Cultural Requirements for Autonomous Agents. CoRR (2023)
Misael Alpizar Santana, Radu Calinescu, Colin Paterson
Risk-aware Real-time Object Detection. EDCC (2022)
Mario Gleirscher, Radu Calinescu, James A. Douthwaite, Benjamin Lesage, Colin Paterson, Jonathan M. Aitken, Rob Alexander, James Law
Verified synthesis of optimal safety controllers for human-robot collaboration. Sci. Comput. Program. 218 (2022)
Xinwei Fang, Radu Calinescu, Colin Paterson, Julie Wilson
PRESTO: Predicting System-level Disruptions through Parametric Model Checking. CoRR (2022)
Naif Alasmari, Radu Calinescu, Colin Paterson, Raffaela Mirandola
Quantitative verification with adaptive uncertainty reduction. J. Syst. Softw. 188 (2022)
Xinwei Fang, Radu Calinescu, Colin Paterson, Julie Wilson
PRESTO: Predicting System-level Disruptions through Parametric Model Checking. SEAMS (2022)
Beverley Townsend, Colin Paterson, T. T. Arvind, Gabriel Nemirovsky, Radu Calinescu, Ana Cavalcanti, Ibrahim Habli, Alan Thomas
From Pluralistic Normative Principles to Autonomous-Agent Rules. Minds Mach. 32 (4) (2022)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Assured Multi-agent Reinforcement Learning with Robust Agent-Interaction Adaptability. KES-IDT (2022)
Misael Alpizar Santana, Radu Calinescu, Colin Paterson
Mitigating Risk in Neural Network Classifiers. SEAA (2022)
Richard Hawkins, Colin Paterson, Chiara Picardi, Yan Jia, Radu Calinescu, Ibrahim Habli
Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS). CoRR (2021)
Rob Ashmore, Radu Calinescu, Colin Paterson
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges. ACM Comput. Surv. 54 (5) (2021)
Colin Paterson, Radu Calinescu, Chiara Picardi
Detection and Mitigation of Rare Subclasses in Deep Neural Network Classifiers. AITest (2021)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Assured Deep Multi-Agent Reinforcement Learning for Safe Robotic Systems. ICAART (Revised Selected Papers) (2021)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Reinforcement Learning with Quantitative Verification for Assured Multi-Agent Policies. ICAART (2) (2021)
Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
Utilising Assured Multi-Agent Reinforcement Learning within Safety-Critical Scenarios. KES (2021)
Danny Weyns, Bradley R. Schmerl, Masako Kishida, Alberto Leva, Marin Litoiu, Necmiye Ozay, Colin Paterson, Kenji Tei
Towards Better Adaptive Systems by Combining MAPE, Control Theory, and Machine Learning. SEAMS@ICSE (2021)
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. CoRR (2021)
Radu Calinescu, Colin Paterson, Kenneth Johnson
Efficient Parametric Model Checking Using Domain Knowledge. IEEE Trans. Software Eng. 47 (6) (2021)
Naif Alasmari, Radu Calinescu, Colin Paterson, Raffaela Mirandola
Quantitative Verification with Adaptive Uncertainty Reduction. CoRR (2021)
Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. SAFECOMP (2021)
Danny Weyns, Bradley R. Schmerl, Masako Kishida, Alberto Leva, Marin Litoiu, Necmiye Ozay, Colin Paterson, Kenji Tei
Towards Better Adaptive Systems by Combining MAPE, Control Theory, and Machine Learning. CoRR (2021)
Mario Gleirscher, Radu Calinescu, James A. Douthwaite, Benjamin Lesage, Colin Paterson, Jonathan M. Aitken, Rob Alexander, James Law
Verified Synthesis of Optimal Safety Controllers for Human-Robot Collaboration. CoRR (2021)
Colin Paterson, Radu Calinescu
Observation-Enhanced QoS Analysis of Component-Based Systems. IEEE Trans. Software Eng. 46 (5) (2020)
Chiara Picardi, Colin Paterson, Richard Hawkins, Radu Calinescu, Ibrahim Habli
Assurance Argument Patterns and Processes for Machine Learning in Safety-Related Systems. SafeAI@AAAI (2020)
Lydia Gauerhof, Richard Hawkins, Chiara Picardi, Colin Paterson, Yuki Hagiwara, Ibrahim Habli
Assuring the Safety of Machine Learning for Pedestrian Detection at Crossings. SAFECOMP (2020)
Colin Paterson, Radu Calinescu
Detection and Mitigation of Rare Subclasses in Neural Network Classifiers. CoRR (2019)
Chiara Picardi, Richard Hawkins, Colin Paterson, Ibrahim Habli
A Pattern for Arguing the Assurance of Machine Learning in Medical Diagnosis Systems. SAFECOMP (2019)
Radu Calinescu, Javier Cámara, Colin Paterson
Socio-cyber-physical systems: models, opportunities, open challenges. SEsCPS@ICSE (2019)
Rob Ashmore, Radu Calinescu, Colin Paterson
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges. CoRR (2019)
Colin Paterson, Radu Calinescu, Di Wang, Suresh Manandhar
Using unstructured data to improve the continuous planning of critical processes involving humans. SEAMS@ICSE (2019)
Colin Paterson, Radu Calinescu
Observation-Enhanced QoS Analysis of Component-Based Systems. CoRR (2018)
Radu Calinescu, Kenneth Johnson, Colin Paterson
Efficient parametric model checking using domain-specific modelling patterns. ICSE (NIER) (2018)
Radu Calinescu, Colin Paterson, Kenneth Johnson
Efficient Parametric Model Checking Using Domain Knowledge. CoRR (2018)
Carlos Eduardo da Silva, Jose Diego Saraiva da Silva, Colin Paterson, Radu Calinescu
Self-Adaptive Role-Based Access Control for Business Processes. SEAMS@ICSE (2017)
Colin Paterson, Radu Calinescu
Accurate Analysis of Quality Properties of Software with Observation-Based Markov Chain Refinement. ICSA (2017)
Radu Calinescu, Kenneth Johnson, Colin Paterson
FACT: A Probabilistic Model Checker for Formal Verification with Confidence Intervals. TACAS (2016)
Radu Calinescu, Simos Gerasimou, Kenneth Johnson, Colin Paterson
Using Runtime Quantitative Verification to Provide Assurance Evidence for Self-Adaptive Software - Advances, Applications and Research Challenges. Software Engineering for Self-Adaptive Systems (2013)
Colin Paterson, Ruud H. Teunter, Kevin D. Glazebrook
Enhanced lateral transshipments in a multi-location inventory system. Eur. J. Oper. Res. 221 (2) (2012)
Colin Paterson, Gudrun P. Kiesmüller, Ruud H. Teunter, Kevin D. Glazebrook
Inventory models with lateral transshipments: A review. Eur. J. Oper. Res. 210 (2) (2011)