Project ID: STAI-CDT-2023-IC-9
Themes: AI Planning, Logic
Supervisor: Dr Marek Rei
Large language models have become the main backbone of most state-of-the-art NLP systems. By pre-training on very large datasets with unsupervised objectives, these models are able to learn good representations for language...
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Project ID: STAI-CDT-2023-KCL-30
Themes: Logic, Verification
Supervisor: Dr Hector Menendez Benito, Dr Karine Even Mendoza
The issue of machine learning trust is a pressing concern that has brought together multiple communities to tackle it. With the increasing use of tools such as ChatGPT and the identification of fairness issues, ensuring the...
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Project ID: STAI-CDT-2023-IC-6
Themes: Logic, Verification
Supervisor: Dr Francesco Belardinelli
In many games the outcome of the players’ actions is given stochastically rather than deterministically, e.g., in card games, board games with dice (Risk!), etc.However, the literature of logic-based languages for...
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Project ID: STAI-CDT-2023-IC-5
Themes: Logic, Verification
Supervisor: Dr Francesco Belardinelli
Deep Reinforcement Learning (DRL) has proved to be a powerful technique that allows autonomous agents to learn optimal behaviours (aka policies) in unknown and complex environments through models of rewards and...
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Project ID: STAI-CDT-2023-KCL-26
Themes: Logic, Verification
Supervisor: David Watson
Causal reasoning is essential to decision-making in real-world problems. However, observational data is rarely sufficient to infer causal relationships or estimate treatment effects due to confounding signals. Pearl (2009)...
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Project ID: STAI-CDT-2023-KCL-19
Themes: Logic, Verification
Supervisor: Mohammad Abdulaziz
Matching is a fundamental problem in combinatorial optimisation with multiple applications in AI, like in belief propagation [10], multi-agent resource allocation algorithms [6], and constraint solving [16], and in...
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Project ID: STAI-CDT-2023-IC-4
Themes: Logic, Norms, Reasoning
Supervisor: Pedro Mediano
Neurosymbolic systems seek to combine the strengths of two major classes of AI algorithms: neural networks, able to recognise patterns in unstructured data, and logic-based systems, capable of powerful reasoning. One of the...
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Project ID: STAI-CDT-2023-KCL-25
Themes: Logic, Norms, Reasoning
Supervisor: Yulan He
Recent efforts to Natural Language Understanding (NLU) have been largely exemplified in tasks such as natural language inference, reading comprehension and question answering. We have witnessed the shift of paradigms in NLP...
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Project ID: STAI-CDT-2023-KCL-18
Themes: Logic
Supervisor: Nicola Paoletti
Temporal logic (TL) is arguably the primary language for formal specification and reasoning about system correctness and safety. They enable the specification and verification of properties such as “will the agent...
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Project ID: STAI-CDT-2023-KCL-24
Themes: Logic, Verification
Supervisor: Hana Chockler
We developed a framework for causal explanations of image classifiers based on the principled approach of actual causality [1] and responsibility [2], the latter pioneered by Dr Chockler. Our framework already resulted in a...
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Project ID: STAI-CDT-2023-KCL-23
Themes: Logic, Verification
Supervisor: Hana Chockler
We developed a framework for causal explanations of image classifiers based on the principled approach of actual causality [1] and responsibility [2], the latter pioneered by Dr Chockler. Our framework already resulted in a...
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Project ID: STAI-CDT-2023-KCL-22
Themes: Logic
Supervisor: Sanjay Modgil, Odinaldo Rodrigues
An important long-term concern regarding the ethical impact of AI is the so called ‘value alignment problem’; that is, how to ensure that the decisions of autonomous AIs are aligned with human values. Addressing...
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