• Discrete-continuous hybrid planning for adaptive systems

    Project ID: STAI-CDT-2021-IC-15
    Themes: AI Planning, Reasoning, Verification
    Supervisor: Antonio Filieri

    Adaptive cyber-physical systems rely on the composition and coordinated interaction of different decision-making procedures, each typically realized with specific AI methods. Cyber components capabilities and semantics are...

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  • Neural-symbolic Reinforcement Learning.

    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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  • Model Checking Agents that Learn

    Project ID: STAI-CDT-2021-IC-3
    Themes: AI Planning, Verification
    Supervisor: Francesco Belardinelli

    In Reinforcement Learning (RL) autonomous agents have typically to choose their actions in order to maximise some notion of cumulative reward [1]. Tools and techniques for RL have been applied successfully to domain as...

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  • Data-Driven and Explainable Discrete Optimization for Effective Transportation in Healthcare

    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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  • Enhancing Scale and Performance of Safe and Trusted Multi-Agent Planning

    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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  • Safe Rational Interactions in Data-driven Control

    Project ID: STAI-CDT-2021-IC-8
    Themes: AI Planning, Logic, Verification
    Supervisor: Alessio Lomuscio

    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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  • Correct-by-construction domain-specific AI planners

    Project ID: STAI-CDT-2021-KCL-4
    Themes: AI Planning, Verification
    Supervisor: Steffen Zschaler

    When using complex algorithms to make decisions within autonomous systems, the weak link is the abstract model used by the algorithms: any errors in the model may lead to unanticipated behaviour potentially risking...

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