The overarching objective of this project is to endow autonomous systems with advanced decision-making capabilities and collaboration skills. We aim to build artificial systems that, in real-world environments, are capable of reasoning about high-level goals specified by human operators and formulating, in collaboration with them, a course of actions to successfully achieve such goals. Strategic reasoning and fluid teaming are fundamental skills of cognitive systems: they are needed in a variety of situations, from day-to-day tasks such as assisting humans in household chores, to extreme missions, such as space exploration. The techniques that we propose are general and can be used to support both robotic systems and software agents. We choose disaster response operations where unmanned aerial vehicles (UAVs) assist emergency responders as our demonstration arena. In this domain, in fact, it is crucial for the UAVs to think strategically to pursue goals efficiently and to act in concert with the human operators who are ultimately in charge of critical decisions. The primary objective of the project is broken down into two strands. The first is to equip artificial artefacts that operate in real-world settings with the ability to reason about themselves and the world around them to determine plans for achieving high-level goals efficiently and robustly. Planning is a key component of intelligence and one of the most traditional fields of artificial intelligence (AI). Planning has achieved impressive results in idealised settings where the world is deterministic, and actions are instantaneous. However, planning in real-world environments in which temporal constraints and uncertainty cannot be ignored remains very challenging. Currently, no single temporal planner exhibits strong performance and, at the same time, handles all the features needed to represent practical problems. This project aims to contribute to filling this gap. On the one hand, we will investigate how different representations of temporal planning problems impact the performances of existing planners and whether there is one representation that facilitates efficient and flexible reasoning. On the other hand, we will formulate efficient algorithms that support advanced features of temporal reasoning such as required concurrency, timed transitions and uncontrollable action durations. The second strand of this project emerges from the observation that, in any complex real-world operations, artificial artefacts rarely operate in isolation from humans. For the humans and the agents to team up in a fluidly and trustworthy, it is crucial that the agents' decision-making is intelligible to the human operators and also receptive to inputs from them. In this project, we explore the idea that planning can play a pivotal role in achieving intelligibility in autonomous systems. We consider two different facets of intelligibility: ex-post intelligibility, or explainability, whereby the system can exhibit the information and the logic that it has used to arrive at its decisions; and ex-ante intelligibility, or transparency, whereby the system exposes how it operates to a human operator in such a way that the operator can intervene and negotiate with the system a different course of actions. We investigate how planning and computational argumentation can be blended to achieve both ex-post and ex-ante intelligibility. Argumentation refers to a set of techniques for evaluating claims by considering reasons for and against them through logical reasoning. Argumentation techniques based on planning will empower the agent with the capacity to exhibit arguments in support of its decisions as well as to negotiate with the operator a change in the plan if needed. Providing advances in the planning and collaboration skills of autonomous systems would benefit research in planning, AI and robotics and, more crucially, promote their broad adoption in real-world contexts.

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

The proposed Instant Knowledge (IK) project is about providing up to date and relevant data to users throughout an organisation. Such information will be continually changing. Moreover, the network that is created to access this data will have to cater for mobile terminals. In such a dynamic environment techniques such as data mining will be used to automatically maintain the data sources. Thus, the data provider will not be actively involved in releasing information to remote users. Of course the data provider may refuse to release any sensitive information but that would severely limit the usefulness of the IK network. On the other hand, if the information contains sensitive company data or personal identifying information (PII) relating to the provider or third parties, then it cannot be released without controlling who has access rights. The central research problem therefore is how to control access to dynamic information in a complex dynamic environment. Our first task is to identify the system requirements and from this determine potential threats to the system. These threats may be from accidental leaking of data or more malicious attacks on the system. Once the threats have been identified, in order to focus our research we need to understand what the major threats are, and what are likely to have less impact. This analysis will be carried out in collaboration with the industrial partners and will determine the overall security requirements for the project. The second task will focus on designing security protocols to meet the above requirements. One area we will investigate is the field of Trusted Computing (TC). This subject is normally associated with software licensing and protecting multi-media content, but the same technology can be adapted to protect the PII distributed within the IK network. Many protocols exist that will confirm the identity of the party that data is being sent to, but which offer no guarantee that the recipient will subsequently protect that information. What TC provides are mechanisms to seal data so that it is only exposed when the platform is in a specific configuration. Thus the owner of the data retains control of this even after it has been released - the trust required of the recipient is greatly diminished. TC technology exists for static platforms, but standards for mobile platforms were only released in July 2007. The research challenge is to identify the components for a trusted mobile platform to support our protocols. The difficulty lies in adapting technologies for static platforms, such as virtual machines, to a more resource limited Trusted Mobile Platform (TMP). Based on this TMP, our research will focus on how security policies that determine access to data can be enforced. Mechanisms exist for policy enforcement on standard platforms, but without TC they assume a high level of trust in the Policy Enforcement Point (PEP) and the entity running this device. We seek to exploit Mobile TC to strengthen the PEP on mobile devices. Some form of authentication is often required before data is released. We will investigate how a TMP will allow authentication based on entities' attributes rather than identity. Moreover we will investigate how the DAA protocol can be exploited to provide a further degree of user anonymity. This protocol can attest that a platform can be trusted without revealing any PII. We will also investigate how the TMP can be used to provide data provenance. In all of the above we will collaborate with other groups to produce a demonstrator system. As this develops adjustments may be made to the initial system design. We will therefore continuously monitor developments and repeat security analysis as we progress, reviewing and modifying requirements with the industrial partners. The final stage of our research will be to carry out a rigorous security analysis of the final system to ensure that all our security requirements are met.

We study cryptanalysis of cryptographic schemes using lattice reduction, efficient construction of lattice based encryption schemes (e.g. for embedded devices), and theoretical aspects for proving the security of encryption schemes against adversaries with access to a general-purpose quantum computer. Our approach includes theoretical analysis and concrete experiments

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.