Domenico Corapi

Imperial College London, Londinium, England, United Kingdom

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Publications (11)0.29 Total impact

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    ABSTRACT: Environment domain models are a key part of the information used by adaptive systems to determine their behaviour. These models can be incomplete or inaccurate. In addition, since adaptive systems generally operate in environments which are subject to change, these models are often also out of date. To update and correct these models, the system should observe how the environment responds to its actions, and compare these responses to those predicted by the model. In this paper, we use a probabilistic rule learning approach, NoMPRoL, to update models using feedback from the running system in the form of execution traces. NoMPRoL is a technique for nonmonotonic probabilistic rule learning based on a transformation of an inductive logic programming task into an equivalent abductive one. In essence, it exploits consistent observations by finding general rules which explain observations in terms of the conditions under which they occur. The updated models are then used to generate new behaviour with a greater chance of success in the actual environment encountered.
    Software Engineering (ICSE), 2013 35th International Conference on; 01/2013
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    ABSTRACT: Normative frameworks provide a means to address the governance of open systems, by offering a mechanism to express responsibilities and permissions of the individual participants with respect to the entire system without compromising their autonomy. Careful design is crucial if it is to meet its requirements. Tools that support the design process can be of great benefit. In this paper, we describe a method for choosing the appropriate change in the normative specification, using impact analysis of the critical consequences being preserved or rejected by the change.
    Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3; 06/2012
  • Domenico Corapi, Alessandra Russo, Emil Lupu
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    ABSTRACT: In this paper we discuss the design of an Inductive Logic Programming (ILP) system in Answer Set Programming (ASP) and more in general the problem of integrating the two. We show how to formalise the learning problem as an ASP program and provide details on how the optimisation features of modern solvers can be adapted to derive preferred hypotheses.
    Proceedings of the 21st international conference on Inductive Logic Programming; 07/2011
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    ABSTRACT: In this paper we propose a use-case-driven iterative design methodology for normative frameworks, also called virtual institutions, which are used to govern open systems. Our computational model represents the normative framework as a logic program under answer set semantics (ASP). By means of an inductive logic programming approach, implemented using ASP, it is possible to synthesise new rules and revise the existing ones. The learning mechanism is guided by the designer who describes the desired properties of the framework through use cases, comprising (i) event traces that capture possible scenarios, and (ii) a state that describes the desired outcome. The learning process then proposes additional rules, or changes to current rules, to satisfy the constraints expressed in the use cases. Thus, the contribution of this paper is a process for the elaboration and revision of a normative framework by means of a semi-automatic and iterative process driven from specifications of (un)desirable behaviour. The process integrates a novel and general methodology for theory revision based on ASP.
    Theory and Practice of Logic Programming 07/2011; 11. · 0.29 Impact Factor
  • Computational Logic in Multi-Agent Systems - 12th International Workshop, CLIMA XII, Barcelona, Spain, July 17-18, 2011. Proceedings; 01/2011
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    ABSTRACT: Recent years have seen a significant increase in the popularity of social networking services. These online services enable users to construct groups of contacts, referred to as friends, with which they can share digital content and communicate. This sharing is actively encouraged by the social networking services, with users' privacy often seen as a secondary concern. In this paper we first propose a privacy-aware social networking service and then introduce a collaborative approach to authoring privacy policies for the service. In addressing user privacy, our approach takes into account the needs of all parties affected by the disclosure of information and digital content.
    Policies for Distributed Systems and Networks (POLICY), 2010 IEEE International Symposium on; 08/2010
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    ABSTRACT: The online presence projected by a person is comprised of all the information about them available on the Internet. In online communities and social networking services, it is often possible for third-parties to modify this content by, for example, commenting on existing content or uploading new content. This has the potential to negatively impact the privacy of a presence owner (the person referred to by the on-line content) by disclosing information about them without consent. In this paper we propose a Privacy Butler, an automated service that can monitor a person's online presence and attempt to make corrections based on policies specified by the owner of the online presence.
    Pervasive Computing and Communications Workshops (PERCOM Workshops), 2010 8th IEEE International Conference on; 05/2010
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    Domenico Corapi, Alessandra Russo, Emil Lupu
    Technical Communications of the 26th International Conference on Logic Programming, ICLP 2010, July 16-19, 2010, Edinburgh, Scotland, UK; 01/2010
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    Business Process Management Workshops - BPM 2010 International Workshops and Education Track, Hoboken, NJ, USA, September 13-15, 2010, Revised Selected Papers; 01/2010
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    ABSTRACT: In the physical world, the rules governing behaviour are debugged by observing an outcome that was not intended and the addition of new constraints to prevent the attainment of that outcome. We propose a similar approach to support the incremental development of normative frameworks (also called institutions) and demonstrate how this works through the validation and synthesis of normative rules using model generation and inductive learning. This is achieved by the designer providing a set of use cases, comprising collections of event traces that describe how the system is used along with the desired outcome with respect to the normative framework. The model generator encodes the description of the current behaviour of the system. The current specification and the traces for which current behaviour and expected behaviour do not match are given to the learning framework to propose new rules that revise the existing norm set in order to inhibit the unwanted behaviour. The elaboration of a normative system can then be viewed as a semi-automatic, iterative process for the detection of incompleteness or incorrectness of the existing normative rules, with respect to desired properties, and the construction of potential additional rules for the normative system.
    Coordination, Organizations, Institutions, and Norms in Agent Systems VI - COIN 2010 International Workshops, COIN@AAMAS 2010, Toronto, Canada, May 2010, COIN@MALLOW 2010, Lyon, France, August 2010, Revised Selected Papers; 01/2010
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    ABSTRACT: Pervasive computing requires infrastructures that adapt to changes in user behaviour while minimising user interactions. Policy-basedapproaches have been proposed as a means of providing adaptability but, at present, require policy goals and rules to be explicitly defined by users. This paper presents a novel, logic-based approach for automatically learning and updating models of users from their observed behaviour. We show how this task can be accomplished using a nonmonotonic learning system, and we illustrate how the approach can be exploited within a pervasive computing framework.
    01/2009;