Project ID: STAI-CDT-2022-KCL-3
Themes: Logic, Norms, Verification
Supervisor: Hana Chockler
The goal of this project is to develop a causality-based framework for the analysis of decentralised finance (DeFi), based on the principled approach of actual causality [1] and responsibility [2], the latter pioneered by...
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Project ID: STAI-CDT-2022-KCL-2
Themes: AI Provenance, Logic
Supervisor: Albert Meroño Peñuela, Barbara McGillivray
Language models learned from data have become prevalent in AI systems, but they are sensitive to the identification of undesired behaviour posing risks to society, like offensive language. The task of automatic detection of...
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Project ID: STAI-CDT-2022-IC-3
Themes: Logic, Verification
Supervisor: Francesco Belardinelli
Reinforcement Learning, and its extension Deep Reinforcement Learning (DRL), are Machine Learning (ML) techniques that allow autonomous agents to learn optimal behaviours (called policies) in unknown and complex...
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Project ID: STAI-CDT-2022-IC-4
Themes: Logic, Verification
Supervisor: Francesco Belardinelli
Reinforcement Learning (RL) is a technique widely used to allow agents to learn behaviours based on a reward/punishment mechanism [1]. In combination with methods from deep learning, RL is currently applied in a number of...
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Project ID: STAI-CDT-2022-IC-2
Themes: Logic, Norms
Supervisor: Alessandra Russo
Within the last two decades, Deep Learning has been demonstrated to achieve high accuracy in computational tasks that involve large quantities of data and for which manual feature extraction would be difficult to handle,...
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Project ID: STAI-CDT-2022-ICL-1
Themes: Logic, Verification
Supervisor: Prof Nobuko Yoshida
Today, most computer applications are developed as ensembles of concurrent multi-agents (or components), that communicate via message passing across some network. Modern programming languages and toolkits provide...
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Project ID: STAI-CDT-2021-IC-24
Themes: AI Planning, Logic, Verification
Supervisor: Francesco Belardinelli
The growing societal impact of AI-based systems has brought with it a set of risks and concerns [1, 2].Indeed, unintended and harmful behaviours may emerge from the application of machine learning (ML) algorithms, including...
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Project ID: STAI-CDT-2021-IC-23
Themes: AI Planning, Logic, Verification
Supervisor: Francesco Belardinelli
The growing societal impact of AI-based systems has brought with it a set of risks and concerns [1, 2].Indeed, unintended and harmful behaviours may emerge from the application of machine learning (ML) algorithms, including...
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Project ID: STAI-CDT-2021-IC-22
Themes: AI Planning, Logic, Verification
Supervisor: Francesco Belardinelli
The growing societal impact of AI-based systems has brought with it a set of risks and concerns [1, 2].Indeed, unintended and harmful behaviours may emerge from the application of machine learning (ML) algorithms, including...
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Project ID: STAI-CDT-2021-IC-21
Themes: Logic, Verification
Supervisor: Dalal Alrajeh
Recent times have witnessed a flurry of advancements in ML, enabling their widespread application in domains such healthcare, security and autonomous vehicles. However, their deployment has also come at cost, resulting in...
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Project ID: STAI-CDT-2021-IC-20
Themes: AI Planning, Logic, Verification
Supervisor: Dalal Alrajeh
AI Planning is concerned with producing plans that are guaranteed to achieve a robot’s goals, assuming the pre-specified assumptions about the environment in which it operates hold. However, no matter how detailed these...
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Project ID: STAI-CDT-2021-KCL-12
Themes: AI Provenance, Logic
Supervisor: Albert Meroño Peñuela
Ontologies have become fundamental AI artifacts in providing knowledge to intelligent systems. The concepts and relationships formalised in these ontologies are frequently used to semantically annotate data, helping...
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