Project ID: STAI-CDT-2022-KCL-10
Themes: AI Planning, Logic, Verification
Supervisor: Mohammad Abdulaziz
Constructing a world-model is a fundamental part of model-based AI, e.g. planning. Usually, such a model is constructed by a human modeller and it should capture the modeller’s intuitive understanding of the world dynamics...
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Project ID: STAI-CDT-2022-KCL-7
Themes: AI Planning
Supervisor: Martim Brandao, Yali Du
Motion planning algorithms are crucial components of real-world robots: whether in manufacturing, hospital and service robots, inspection, warehouse or other applications. These algorithms compute sequences of movements...
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Project ID: STAI-CDT-2022-KCL-4
Themes: AI Planning
Supervisor: Matteo Leonetti
Exploration in Reinforcement Learning (RL) consists in taking actions that are currently considered suboptimal by the agent. The agent continually adjusts its estimate of the value of actions and, if a new action proves to...
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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-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-15
Themes: AI Planning, Verification
Supervisor: Kevin Lano
Machine learning (ML) approaches such as encoder-decoder networks and LSTM have been successfully used for numerous tasks involving translation or prediction of information (Otter et al, 2020). However, the knowledge...
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Project ID: STAI-CDT-2021-IC-2
Themes: AI Planning, Logic
Supervisor: Alessandra Russo
Recent advances in deep reinforcement learning (DRL) have allowed computer programs to beat humans at complex games like Chess or Go years before the original projections. However, the SOTA in DRL misses out on some of the...
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Project ID: STAI-CDT-2021-KCL-3
Themes: AI Planning, Argumentation, Scheduling
Supervisor: Dimitrios Letsios
This project aims to contribute to the development of safe and trusted, artificially intelligent transportation in healthcare. The London Ambulance Service (LAS) operates more than 1100 ambulances to respond to medical...
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Project ID: STAI-CDT-2021-IC-5
Themes: AI Planning
Supervisor: Wayne Luk
Cooperative Multi-Agent Planning (MAP) is a topic in symbolic artificial intelligence (AI). In a cooperative MAP system, multiple agents collaborate to achieve a common goal. A cooperative MAP solver produces...
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Project ID: STAI-CDT-2021-IC-8
Themes: AI Planning, Logic, Verification
Supervisor: Alessio Lomuscio, David Angeli
In autonomous and multi-agent systems players are normally assumed rational and cooperating or competing in groups to achieve their overall objectives. Useful methods to study the resulting interactions come from game...
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