A review of particle swarm optimization. Part I: background and development. - Alec Banks; Jonathan Vincent; Chukwudi Anyakoha (Nat. Comput., 2007)

A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications. - Alec Banks; Jonathan Vincent; Chukwudi Anyakoha (Nat. Comput., 2008)

Natural strategies for search. - Alec Banks; Jonathan Vincent; Keith Phalp (Nat. Comput., 2009)

A framework of requirements for the design and management of dependable network enabled capability system of systems. - Alec Banks; Neil Bowman; Paul Caseley (SoSE, 2010)

Hybridisation of particle swarm optimisation with area concentrated search. - Alec Banks; Jonathan Vincent (Int. J. Knowl. Based Intell. Eng. Syst., 2010)

Efficient runtime quantitative verification using caching, lookahead, and nearly-optimal reconfiguration. - Simos Gerasimou; Radu Calinescu; Alec Banks (SEAMS, 2014)

Self-adaptive Software with Decentralised Control Loops. - Radu Calinescu; Simos Gerasimou; Alec Banks (FASE, 2015)

Assured Reinforcement Learning with Formally Verified Abstract Policies. - George Mason; Radu Calinescu; Daniel Kudenko; Alec Banks (ICAART (2), 2017)

Requirements Assurance in Machine Learning. - Alec Banks; Rob Ashmore (SafeAI@AAAI, 2019)

A Safety Framework for Critical Systems Utilising Deep Neural Networks. - Xingyu Zhao 001; Alec Banks; James Sharp; Valentin Robu; David Flynn; Michael Fisher 001; Xiaowei Huang 001 (SAFECOMP, 2020)

Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems for Robotics. - Wei Huang 035; Yifan Zhou; Youcheng Sun; Alec Banks; Jie Meng; James Sharp; Simon Maskell; Xiaowei Huang 001 (CoRR, 2020)

The Utility of Neural Network Test Coverage Measures. - Rob Ashmore; Alec Banks (SafeAI@AAAI, 2021)

Reinforcement Learning with Quantitative Verification for Assured Multi-Agent Policies. - Joshua Riley; Radu Calinescu; Colin Paterson; Daniel Kudenko; Alec Banks (ICAART (2), 2021)

Assured Deep Multi-Agent Reinforcement Learning for Safe Robotic Systems. - Joshua Riley; Radu Calinescu; Colin Paterson; Daniel Kudenko; Alec Banks (ICAART (Revised Selected Papers), 2021)

Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles. - Xingyu Zhao 001; Wei Huang 035; Alec Banks; Victoria Cox; David Flynn; Sven Schewe; Xiaowei Huang 001 (AISafety@IJCAI, 2021)

Utilising Assured Multi-Agent Reinforcement Learning within Safety-Critical Scenarios. - Joshua Riley; Radu Calinescu; Colin Paterson; Daniel Kudenko; Alec Banks (KES, 2021)

Reliability Assessment and Safety Arguments for Machine Learning Components in Assuring Learning-Enabled Autonomous Systems. - Xingyu Zhao 001; Wei Huang 035; Vibhav Bharti; Yi Dong 002; Victoria Cox; Alec Banks; Sen Wang 002; Sven Schewe; Xiaowei Huang 001 (CoRR, 2021)

Assured Multi-agent Reinforcement Learning with Robust Agent-Interaction Adaptability. - Joshua Riley; Radu Calinescu; Colin Paterson; Daniel Kudenko; Alec Banks (KES-IDT, 2022)

Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance. - Yi Dong 002; Wei Huang 035; Vibhav Bharti; Victoria Cox; Alec Banks; Sen Wang 002; Xingyu Zhao 001; Sven Schewe; Xiaowei Huang 001 (ACM Trans. Embed. Comput. Syst., 2023)

Removing the Big Red Button: Uncrewed Ground Vehicles in Complex Military Environments. - Alec Banks; Prathyush P. Menon; Steve Austen (ISSRE (Workshops), 2024)

Adaptive Human-Swarm Interaction based on Workload Measurement using Functional Near-Infrared Spectroscopy. - Ayodeji Opeyemi Abioye; Aleksandra Landowska; William Hunt; Horia A. Maior; Sarvapali D. Ramchurn; Mohammad Naiseh; Alec Banks; Mohammad Divband Soorati (CoRR, 2024)

Hierarchical Distribution-aware Testing of Deep Learning. - Wei Huang 035; Xingyu Zhao 001; Alec Banks; Victoria Cox; Xiaowei Huang 001 (ACM Trans. Softw. Eng. Methodol., 2024)