Search Results for author: Simos Gerasimou

Found 8 papers, 3 papers with code

Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding

1 code implementation28 May 2024 Daniel Bethell, Simos Gerasimou, Radu Calinescu, Calum Imrie

Empowering safe exploration of reinforcement learning (RL) agents during training is a critical impediment towards deploying RL agents in many real-world scenarios.

reinforcement-learning Reinforcement Learning (RL) +2

DeepKnowledge: Generalisation-Driven Deep Learning Testing

no code implementations25 Mar 2024 Sondess Missaoui, Simos Gerasimou, Nikolaos Matragkas

Despite their unprecedented success, DNNs are notoriously fragile to small shifts in data distribution, demanding effective testing techniques that can assess their dependability.

DNN Testing

Robust Uncertainty Quantification Using Conformalised Monte Carlo Prediction

1 code implementation18 Aug 2023 Daniel Bethell, Simos Gerasimou, Radu Calinescu

Deploying deep learning models in safety-critical applications remains a very challenging task, mandating the provision of assurances for the dependable operation of these models.

Conformal Prediction Decision Making +1

Bayesian Learning for the Robust Verification of Autonomous Robots

1 code implementation15 Mar 2023 Xingyu Zhao, Simos Gerasimou, Radu Calinescu, Calum Imrie, Valentin Robu, David Flynn

Autonomous robots used in infrastructure inspection, space exploration and other critical missions operate in highly dynamic environments.

Fast Parametric Model Checking through Model Fragmentation

no code implementations2 Feb 2021 Xinwei Fang, Radu Calinescu, Simos Gerasimou, Faisal Alhwikem

Parametric model checking (PMC) computes algebraic formulae that express key non-functional properties of a system (reliability, performance, etc.)

Software Engineering Formal Languages and Automata Theory Robotics

Genetic Improvement @ ICSE 2020

no code implementations31 Jul 2020 William B. Langdon, Westley Weimer, Justyna Petke, Erik Fredericks, Seongmin Lee, Emily Winter, Michail Basios, Myra B. Cohen, Aymeric Blot, Markus Wagner, Bobby R. Bruce, Shin Yoo, Simos Gerasimou, Oliver Krauss, Yu Huang, Michael Gerten

Following Prof. Mark Harman of Facebook's keynote and formal presentations (which are recorded in the proceedings) there was a wide ranging discussion at the eighth international Genetic Improvement workshop, GI-2020 @ ICSE (held as part of the 42nd ACM/IEEE International Conference on Software Engineering on Friday 3rd July 2020).

Importance-Driven Deep Learning System Testing

no code implementations9 Feb 2020 Simos Gerasimou, Hasan Ferit Eniser, Alper Sen, Alper Cakan

Deep Learning (DL) systems are key enablers for engineering intelligent applications due to their ability to solve complex tasks such as image recognition and machine translation.

Machine Translation Translation

DeepFault: Fault Localization for Deep Neural Networks

no code implementations15 Feb 2019 Hasan Ferit Eniser, Simos Gerasimou, Alper Sen

Deep Neural Networks (DNNs) are increasingly deployed in safety-critical applications including autonomous vehicles and medical diagnostics.

Autonomous Vehicles DNN Testing +1

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