Imperial College London

ProfessorAlessandraRusso

Faculty of EngineeringDepartment of Computing

Professor in Applied Computational Logic
 
 
 
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Contact

 

+44 (0)20 7594 8312a.russo Website

 
 
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Location

 

560Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

255 results found

Gabbay DM, Rodrigues OT, Russo A, 2010, Iterating Revision, Publisher: SPRINGER-VERLAG BERLIN, Pages: 105-137, ISSN: 1611-2482

Conference paper

Gabbay DM, Rodrigues OT, Russo A, 2010, Revision, Acceptability and Context Theoretical and Algorithmic Aspects Conclusions and Discussions, REVISION, ACCEPTABILITY AND CONTEXT: THEORETICAL AND ALGORITHMIC ASPECTS, Publisher: SPRINGER-VERLAG BERLIN, Pages: 359-375, ISBN: 978-3-642-14158-4

Book chapter

Corapi D, Russo A, Lupu E, 2010, INDUCTIVE LOGIC PROGRAMMING AS ABDUCTIVE SEARCH, 26th International Conference on Logic Programming (ICLP), Publisher: SCHLOSS DAGSTUHL, LEIBNIZ CENTER INFORMATICS, Pages: 54-63, ISSN: 1868-8969

Conference paper

Maggi FM, Corapi D, Russo A, Lupu E, Visaggio Get al., 2010, Revising Process Models through Inductive Learning., Publisher: Springer, Pages: 182-193

Conference paper

Hosobe H, Satoh K, Ma J, Russo A, Broda Ket al., 2010, Speculative Constraint Processing for Hierarchical Agents, AI Communications: the European journal on artificial intelligence

Journal article

Ma J, Broda K, Goebel R, Hosebe H, Russo Aet al., 2010, Speculative Abductive Reasoning for Hierarchical Agent Systems, 11th Workshop on Computational Logic in Multi-Agent Systems

Conference paper

Alrajeh D, Ray O, Russo A, Uchitel Set al., 2009, Using Abduction and Induction for Operational Requirements Elaboration, Publisher: Elsevier, Pages: 275-288

Conference paper

Charalambides M, Flegkas P, Pavlou G, Rubio-Loyola J, Bandara A, Lupu EC, Russo A, Dulay N, Sloman Met al., 2009, Policy Conflict Analysis for DiffServ Quality of Service Management, IEEE Transactions on Network and Service Management, Vol: 6, Pages: 15-30, ISSN: 1932-4537

Policy-based management provides the ability to (re-)configure differentiated services networks so that desired Quality of Service (QoS) goals are achieved. This requires implementing network provisioning decisions, performing admission control, and adapting bandwidth allocation to emerging traffic demands. A policy-based approach facilitates flexibility and adaptability as policies can be dynamically changed without modifying the underlying implementation. However, inconsistencies may arise in the policy specification. In this paper we provide a comprehensive set of QoS policies for managing Differentiated Services (DiffServ) networks, and classify the possible conflicts that can arise between them. We demonstrate the use of Event Calculus and formal reasoning for the analysis of both static and dynamic conflicts in a semi-automated fashion. In addition, we present a conflict analysis tool that provides network administrators with a user-friendly environment for determining and resolving potential inconsistencies. The tool has been extensively tested with large numbers of policies over a range of conflict types. © 2009 IEEE.

Journal article

Ma J, Russo A, Broda K, Lupu Eet al., 2009, Multi-agent Planning with Confidentiality, 8th Int. Conf. on Autonomous Agents and Multi-Agent Systems

Conference paper

Craven R, Lobo J, Lupu E, Russo A, Sloman Met al., 2009, Security policy refinement using data integration: a position paper., Publisher: ACM, Pages: 25-28

In spite of the wide adoption of policy-based approaches for security management, and many existing treatments of pol- icy verification and analysis, relatively little attention has been paid to policy refinement: the problem of deriving lower-level, runnable policies from higher-level policies, pol- icy goals, and specifications. In this paper we present our initial ideas on this task, using and adapting concepts from data integration. We take a view of policies as governing the performance of an action on a target by a subject, possibly with certain conditions. Transformation rules are applied to these components of a policy in a structured way, in order to translate the policy into more refined terms; the transfor- mation rules we use are similar to those of ‘global-as-view’ database schema mappings, or to extensions thereof. We illustrate our ideas with an example.

Conference paper

Bandara AK, Kakas AC, Lupu EC, Russo Aet al., 2009, Using Argumentation Logic for Firewall Configuration Management, IFIP/IEEE International Symposium on Integrated Network Management (IM 2009), Publisher: IEEE, Pages: 180-+

Conference paper

Corapi D, Ray O, Russo A, Bandara A, Lupu Eet al., 2009, Learning Rules from User Behaviour, 5th IFIP Conference on Artificial Intelligence Applications and Innovations, Publisher: SPRINGER, Pages: 459-+, ISSN: 1571-5736

Conference paper

Alrajeh D, Kramer J, Russo A, Uchitel Set al., 2009, Learning Operational Requirements from Goal Models, 31st International Conference on Software Engineering, ICSE, ISSN: 0270-5257

Conference paper

Kimber T, Broda K, Russo A, 2009, Induction on Failure: Learning Connected Horn Theories, LPNMR09, Logic Programming and Non-Monotonic Reasoning, Pages: 169-181, ISSN: 0302-9743

Conference paper

Broda K, Clark K, Miller R, Russo Aet al., 2009, SAGE: A Logical Agent-Based Environment Monitoring and Control System, 3rd European Conf. on Ambient Intelligence

Conference paper

Craven R, Lobo J, Lupu EC, Ma J, Russo A, Bandara Aet al., 2009, Expressive Policy Analysis with Enhanced System Dynamicity, ASIAN ACM Symposium on Information, Computer and Communications Security (ASIACCS 09), Publisher: ACM, Pages: 239-250

Conference paper

Gabbay D, Rodrigues O, Russo A, 2008, Belief Revision in Non-classical Logics, The Review of Symbolic Logic Journal, Vol: 1, Pages: 267-304

Journal article

Dickens L, Broda K, Russo A, 2008, Transparent modelling of finite stochastic processes for multiple agents, Departmental Technical Report: 08/2, Publisher: Department of Computing, Imperial College London, 08/2

Stochastic Processes are ubiquitous, from automated engineering, through financialmarkets, to space exploration. These systems are typically highly dynamic, unpredictableand resistant to analytic methods; coupled with a need to orchestrate long controlsequences which are both highly complex and uncertain. This report examines some existingsingle- and multi-agent modelling frameworks, details their strengths and weaknesses,and uses the experience to identify some fundamental tenets of good practice in modellingstochastic processes. It goes on to develop a new family of frameworks based on these tenets,which can model single- and multi-agent domains with equal clarity and flexibility, whileremaining close enough to the existing frameworks that existing analytic and learning toolscan be applied with little or no adaption. Some simple and larger examples illustrate thesimilarities and differences of this approach, and a discussion of the challenges inherent indeveloping more flexible tools to exploit these new frameworks concludes matters.

Report

Craven R, Lobo J, Lupu E, Ma J, Russo A, Sloman M, Bandara Aet al., 2008, A formal framework for policy analysis, Departmental Technical Report: 08/5, Publisher: Department of Computing, Imperial College London, 08/5

We present a formal, logical framework for the representation and analysisof an expressive class of authorization and obligation policies. Basic concepts ofthe language and operational model are given, and details of the representationare defined, with an attention to how different classes of policies can be writtenin our framework. We show how complex dependencies amonst policy rules canbe represented, and illustrate how the formalization of policies is joined to adynamic depiction of system behaviour. Algorithmically, we use a species ofabductive, constraint logic programming to analyse for the holding of a numberof interesting properties of policies (coverage, modality conflict, equivalence ofpolicies, etc.). We describe one implementation of our ideas, and conclude withremarks on related work and future research.

Report

Ma K, Broda K, Clark KL, Russo Aet al., 2008, DARE: A System for Distributed Abductive REasoning, Journal of Autonomous Agents and Multi-Agent Systems

Journal article

Alrajeh D, Russo A, Uchitel S, 2008, Deriving non-zeno behavior models from goal models using ILP, 11th International Conference on Fundamental Approaches to Software Engineering, Publisher: SPRINGER-VERLAG BERLIN, Pages: 1-15, ISSN: 0302-9743

Conference paper

Dickens L, Broda K, Russo A, 2008, Modelling MAS as Finite Analytic Stochastic Processes, AISB 2008

Conference paper

Ma J, Broda K, Clark K, Russo Aet al., 2008, A Dynamic System for Distributed Reasoning, International Symposium on Architectures for Intelligent Theory Based Agents

Conference paper

Bandara A, Lobo J, Calo S, Lupu E, Russo A, Sloman Met al., 2007, Toward a Formal Characterization of Policy Specification & Analysis, Annual Conference of ITA (ACITA), Pages: 1-9

Conference paper

Alrajeh D, Ray O, Russo A, Uchitel Set al., 2007, Extracting Requirements from Scenarios using ILP, International Conference on Inductive Logic Programming, Publisher: Springer, Pages: 63-77

Conference paper

Alrajeh D, Ray O, Russo A, Uchitel Set al., 2007, Extracting requirements from scenarios with ILP, 16th International Conference on Inductive Logic Programming, Publisher: SPRINGER-VERLAG BERLIN, Pages: 64-+, ISSN: 0302-9743

Conference paper

Bandara AK, Russo A, Lupu EC, 2007, Towards learning privacy policies, 8th IEEE International Workshop on Policies for Distributed Systems and Networks, Publisher: IEEE COMPUTER SOC, Pages: 274-274

Conference paper

Bandara A, Lupu EC, Russo A, Dulay N, Sloman M, Flegkas P, Charalambides M, Pavlou Get al., 2006, Policy Refinement for DiffServ Quality of Service Management (2006), 9th IFIP/IEEE Intl. Symp. on Integrated Management (IM 2005), Publisher: IEEE

Conference paper

Alrajeh D, Russo A, Uchitel S, 2006, Inferring Operational Requirements from Scenarios and Goal Models Using Inductive Learning (2006), International Workshop on Scenarios and State Machines: Models, Algorithms, and Tools at the 29th IEEE/ACM International Conference on Software Engineering (ICSE). Shanghai, China, 2003.

Conference paper

Charalambides M, Flegkas P, Pavlou G, Bandara A, Dulay N, Lupu EC, Rubio-Loyola J, Russo A, Sloman Met al., 2006, Dynamic Policy Analysis and Conflict Resolution for DiffServ Quality of Service Management (2006), IFIP/IEEE Network Operations and Management Symposium (NOMS 2006), Publisher: IEEE Computer Society

Conference paper

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