1. Cunnington, D., Law, M., Lobo, J., & Russo, A.
    The role of foundation models in neuro-symbolic learning and reasoning. International Conference on Neural-Symbolic Learning and Reasoning, 84–100. (2024)
  2. Parac, R., Nodari, L., Ardon, L., Furelos-Blanco, D., Cerutti, F., & Russo, A.
    Learning Robust Reward Machines from Noisy Labels. In P. Marquis, M. Ortiz, & M. Pagnucco (Eds.), Proceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning, KR 2024, Hanoi, Vietnam. November 2-8, 2024. (2024)
  3. Al-Negheimish, H.
    Towards Numerical Reasoning in Machine Reading Comprehension [PhD thesis, Imperial College London]. (2023)
  4. Al-Negheimish, H., Madhyastha, P., & Russo, A.
    Towards preserving word order importance through Forced Invalidation. Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2555–2562. (2023)
  5. Ardon, L., Furelos-Blanco, D., & Russo, A.
    Learning Reward Machines in Cooperative Multi-Agent Tasks. Proceedings of the Neuro-Symbolic AI for Agent and Multi-Agent Systems (NeSyMAS) Workshop at the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS). (2023)
  6. Baugh, K. G., Cingillioglu, N., & Russo, A.
    Neuro-symbolic Rule Learning in Real-world Classification Tasks. Proceedings of the AAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering (AAAI-MAKE). (2023)
  7. Charalambous, T., Aspis, Y., & Russo, A.
    NeuralFastLAS: Fast Logic-Based Learning from Raw Data. In CoRR: Vol. abs/2310.05145. (2023)
  8. Cunnington, D., Law, M., Lobo, J., & Russo, A.
    FFNSL: Feed-Forward Neural-Symbolic Learner. Machine Learning, 112(2), 515–569. (2023)
  9. Cunnington, D., Law, M., Lobo, J., & Russo, A.
    Neuro-Symbolic Learning of Answer Set Programs from Raw Data. Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI), 3586–3596. (2023)
  10. Furelos-Blanco, D.
    Learning and Exploiting Reward Machines for Reinforcement Learning [PhD thesis, Imperial College London]. (2023)
  11. Furelos-Blanco, D., Law, M., Jonsson, A., Broda, K., & Russo, A.
    Hierarchies of Reward Machines. Proceedings of the International Conference on Machine Learning (ICML), 10494–10541. (2023)
  12. Ielo, A., Law, M., Fionda, V., Ricca, F., Giacomo, G. D., & Russo, A.
    Towards ILP-Based LTLf Passive Learning. Proceedings of the 32nd International Conference on Inductive Logic Programming (ILP), 30–45. (2023)
  13. Jabal, A. A., Bertino, E., Lobo, J., Verma, D. C., Calo, S. B., & Russo, A.
    FLAP - A Federated Learning Framework for Attribute-based Access Control Policies. Proceedings of the 13th ACM Conference on Data and Application Security and Privacy (CODASPY), 263–272. (2023)
  14. Mekhtieva, R. L., Forbes, B., Alrajeh, D., Delaney, B., & Russo, A.
    RECAP-KG: Mining Knowledge Graphs from Raw GP Notes for Remote COVID-19 Assessment in Primary Care. Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium, 1145–1154. (2023)
  15. Mileva, Z., Bikakis, A., D’Asaro, F. A., Law, M., & Russo, A.
    A Unifying Framework for Learning Argumentation Semantics. In CoRR: Vol. abs/2310.12309. (2023)
  16. Seshadri, A. D., & Russo, A.
    Reasoning over the Behaviour of Objects in Video-Clips for Adverb-Type Recognition. In CoRR: Vol. abs/2307.04132. (2023)
  17. Strömfelt, H.
    Consistent and Coherent Relational Representation Learning [PhD thesis, Imperial College London]. (2023)
  18. Tuckey, D.
    Probabilistic Reasoning and Learning for Answer Set Programming [PhD thesis, Imperial College London]. (2023)
  19. Aspis, Y., Broda, K., Lobo, J., & Russo, A.
    Embed2Sym - Scalable Neuro-Symbolic Reasoning via Clustered Embeddings. Proceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning (KR). (2022)
  20. Cingillioglu, N.
    End-to-End Neuro-Symbolic Learning of Logic-based Inference [PhD thesis, Imperial College London]. (2022)
  21. Cunnington, D., Law, M., Lobo, J., & Russo, A.
    Inductive Learning of Complex Knowledge from Raw Data. Proceedings of the AAAI 2022 Fall Symposium on Thinking Fast and Slow and Other Cognitive Theories in AI (TFSOCTAI). (2022)
  22. Jeyakumar, J. V., Dickens, L., Garcia, L., Cheng, Y.-H., Ramirez-Echavarria, D., Noor, J., Russo, A., Kaplan, L. M., Blasch, E., & Srivastava, M. B.
    Automatic Concept Extraction for Concept Bottleneck-based Video Classification. In CoRR: Vol. abs/2206.10129. (2022)
  23. Law, M., Broda, K., & Russo, A.
    Search Space Expansion for Efficient Incremental Inductive Logic Programming from Streamed Data. Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI), 2697–2704. (2022)
  24. Mitchener, L., Tuckey, D., Crosby, M., & Russo, A.
    Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework. Machine Learning, 111(4), 1523–1549. (2022)
  25. Spies, A. F., Russo, A., & Shanahan, M.
    Sparse Relational Reasoning with Object-Centric Representations. Proceedings of the Dynamic Neural Networks Workshop (DyNN) at the 39th International Conference on Machine Learning (ICML). (2022)
  26. Strömfelt, H., Dickens, L., d’Avila Garcez, A. S., & Russo, A.
    Formalizing Consistency and Coherence of Representation Learning. Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), 6873–6885. (2022)
  27. Tuckey, D., Broda, K., & Russo, A.
    A Semantics For Probabilistic Answer Set Programs With Incomplete Stochastic Knowledge. Proceedings of the 15th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOC) at the 38th International Conference on Logic Programming (ICLP). (2022)
  28. Xia, S.
    Neural-Symbolic Learning for Knowledge Base Completion [PhD thesis, Imperial College London]. (2022)
  29. Al-Negheimish, H., Madhyastha, P., & Russo, A.
    Discrete Reasoning Templates for Natural Language Understanding. Student Research Workshop (SRW) at the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL). (2021)
  30. Al-Negheimish, H., Madhyastha, P., & Russo, A.
    Numerical reasoning in machine reading comprehension tasks: are we there yet? Proceedings of the 16th Conference on Empirical Methods in Natural Language Processing (EMNLP), 9643–9649. (2021)
  31. Cingillioglu, N., & Russo, A.
    pix2rule: End-to-end Neuro-symbolic Rule Learning. Proceedings of the 15th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy) at the 1st International Joint Conference on Learning & Reasoning (IJCLR), 15–56. (2021)
  32. Cunnington, D., Law, M., Russo, A., Lobo, J., & Kaplan, L. M.
    Towards Neural-Symbolic Learning to support Human-Agent Operations. Proceedings of the 24th IEEE International Conference on Information Fusion (FUSION), 1–8. (2021)
  33. Drozdov, A., Law, M., Lobo, J., Russo, A., & Don, M. W.
    Online Symbolic Learning of Policies for Explainable Security. Proceedings of the 3rd IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA), 269–278. (2021)
  34. Furelos-Blanco, D., Law, M., Jonsson, A., Broda, K., & Russo, A.
    Induction and Exploitation of Subgoal Automata for Reinforcement Learning. Journal of Artificial Intelligence Research, 70, 1031–1116. (2021)
  35. Law, M., Russo, A., Broda, K., & Bertino, E.
    Scalable Non-observational Predicate Learning in ASP. Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 1936–1943. (2021)
  36. Sautory, T., Cingillioglu, N., & Russo, A.
    HySTER: A Hybrid Spatio-Temporal Event Reasoner. Workshop on Hybrid Artificial Intelligence (HAI) at the 35th AAAI Conference on Artificial Intelligence (AAAI). (2021)
  37. Strömfelt, H., Dickens, L., d’Avila Garcez, A. S., & Russo, A.
    Coherent and Consistent Relational Transfer Learning with Auto-encoders. Proceedings of the 15th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy) at the 1st International Joint Conference on Learning & Reasoning (IJCLR), 176–192. (2021)
  38. Tuckey, D., Russo, A., & Broda, K.
    PASOCS: A Parallel Approximate Solver for Probabilistic Logic Programs under the Credal Semantics. In CoRR: Vol. abs/2105.10908. (2021)
  39. Aspis, Y., Broda, K., Russo, A., & Lobo, J.
    Stable and Supported Semantics in Continuous Vector Spaces. Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR), 59–68. (2020)
  40. Cavezza, D.
    Heuristics for the Refinement of Assumptions in Generalized Reactivity Formulae [PhD thesis, Imperial College London]. (2020)
  41. Cingillioglu, N., & Russo, A.
    Learning Invariants through Soft Unification. Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS), 8186–8197. (2020)
  42. Cunnington, D., Russo, A., Law, M., Lobo, J., & Kaplan, L.
    NSL: Hybrid Interpretable Learning From Noisy Raw Data. In CoRR: Vol. abs/2012.05023. (2020)
  43. Furelos-Blanco, D., Law, M., Russo, A., Broda, K., & Jonsson, A.
    Induction of Subgoal Automata for Reinforcement Learning. Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 3890–3897. (2020)
  44. Gomoluch, P.
    Learning Heuristic Functions and Search Policies for Classical Planning [PhD thesis, Imperial College London]. (2020)
  45. Gomoluch, P., Alrajeh, D., Russo, A., & Bucchiarone, A.
    Learning Neural Search Policies for Classical Planning. Proceedings of the 30th International Conference on Automated Planning and Scheduling (ICAPS), 522–530. (2020)
  46. Jabal, A. A., Bertino, E., Lobo, J., Law, M., Russo, A., Calo, S. B., & Verma, D. C.
    Polisma - A Framework for Learning Attribute-Based Access Control Policies. Proceedings of the 25th European Symposium on Research in Computer Security (ESORICS), 523–544. (2020)
  47. Jabal, A. A., Bertino, E., Lobo, J., Verma, D. C., Calo, S. B., & Russo, A.
    FLAP - A Federated Learning Framework for Attribute-Based Access Control Policies. Proceedings of the AAAI 2020 Fall Symposium on Artificial Intelligence in Government and Public Sector (AAAI-FSS). (2020)
  48. Law, M., Russo, A., Bertino, E., Broda, K., & Lobo, J.
    FastLAS: Scalable Inductive Logic Programming Incorporating Domain-Specific Optimisation Criteria. Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2877–2885. (2020)
  49. Lobo, J., Bertino, E., & Russo, A.
    On Security Policy Migrations. Proceedings of the 25th ACM Symposium on Access Control Models and Technologies (SACMAT), 179–188. (2020)
  50. Pace, D., Russo, A., & Shanahan, M.
    Learning Diverse Representations for Fast Adaptation to Distribution Shift. In CoRR: Vol. abs/2006.07119. (2020)
  51. Rama, O. F., Russo, A., & Broda, K.
    An Architecture For Relational Learning Through Iterative Search Over Hypothesis Space. Knowledge Representation and Reasoning Meets Machine Learning (KR2ML) Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS). (2020)
  52. Russo, A., & Schürr, A.
    Model-Based Software Quality Assurance Tools and Techniques Presented at FASE 2018. Int J Softw Tools Technol Transf, 22(1), 1–2. (2020)
  53. Strömfelt, H., Dickens, L., d’Avila Garcez, A., & Russo, A.
    On the Transferability of VAE Embeddings using Relational Knowledge with Semi-Supervision. In CoRR: Vol. abs/2011.07137. (2020)
  54. Tuckey, D., Broda, K., & Russo, A.
    Towards Structure Learning under the Credal Semantics. Workshop on Probabilistic Logic Programming (PLP) at the 36th International Conference on Logic Programming (ICLP). (2020)
  55. Tuckey, D., Russo, A., & Broda, K.
    A General Framework for Scientifically Inspired Explanations in AI. In CoRR: Vol. abs/2003.00749. (2020)
  56. Xia, S., Broda, K., & Russo, A.
    Topical Neural Theorem Prover That Induces Rules. Proceedings of the 6th Global Conference on Artificial Intelligence (GCAI), 107–120. (2020)
  57. Bertino, E., White, G., Lobo, J., Ingham, J., Cirincione, G. H., Russo, A., Law, M., Calo, S. B., Manotas, I., Verma, D. C., Jabal, A. A., Cunnington, D., & de Mel, G.
    Generative Policies for Coalition Systems - A Symbolic Learning Framework. Proceedings of the 39th IEEE International Conference on Distributed Computing Systems (ICDCS), 1590–1600. (2019)
  58. Cingillioglu, N., & Russo, A.
    DeepLogic: Towards End-to-End Differentiable Logical Reasoning. Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE). (2019)
  59. Cunnington, D., Law, M., Russo, A., Bertino, E., & Calo, S. B.
    Towards a Neural-Symbolic Generative Policy Model. Proceedings of the IEEE International Conference on Big Data (Big Data), 4008–4016. (2019)
  60. Cunnington, D., Manotas, I., Law, M., de Mel, G., Calo, S. B., Bertino, E., & Russo, A.
    A Generative Policy Model for Connected and Autonomous Vehicles. Proceedings of the IEEE Intelligent Transportation Systems Conference (ITSC), 1558–1565. (2019)
  61. Gomoluch, P., Alrajeh, D., & Russo, A.
    Learning Classical Planning Strategies with Policy Gradient. Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS), 637–645. (2019)
  62. Law, M., Russo, A., Bertino, E., Broda, K., & Lobo, J.
    Representing and Learning Grammars in Answer Set Programming. Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2919–2928. (2019)
  63. Law, M., Russo, A., & Broda, K.
    Logic-Based Learning of Answer Set Programs. In Reasoning Web. Explainable Artificial Intelligence (pp. 196–231). (2019)
  64. Tuckey, D., Broda, K., & Russo, A.
    Saliency Maps Generation for Automatic Text Summarization. In CoRR: Vol. abs/1907.05664. (2019)
  65. Verma, D. C., Calo, S. B., Bertino, E., Russo, A., & White, G.
    Policy Based Ensembles for Applying ML on Big Data. Proceedings of the IEEE International Conference on Big Data (Big Data), 4038–4044. (2019)
  66. White, G., Cunnington, D., Law, M., Bertino, E., de Mel, G., & Russo, A.
    A Comparison between Statistical and Symbolic Learning Approaches for Generative Policy Models. Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA), 1314–1321. (2019)
  67. White, G., Ingham, J., Law, M., & Russo, A.
    Using an ASG Based Generative Policy to Model Human Rules. IEEE International Conference on Smart Computing (SMARTCOMP), 99–103. (2019)
  68. Alrajeh, D., & Russo, A.
    Logic-Based Learning: Theory and Application. In Machine Learning for Dynamic Software Analysis: Potentials and Limits (pp. 219–256). (2018)
  69. Aspis, Y., Broda, K., & Russo, A.
    Tensor-Based Abduction in Horn Propositional Programs. Proceedings of the 28th International Conference on Inductive Logic Programming (ILP), 68–75. (2018)
  70. Calo, S. B., Manotas, I., de Mel, G., Cunnington, D., Law, M., Verma, D. C., Russo, A., & Bertino, E.
    AGENP: An ASGrammar-Based GENerative Policy Framework. International Workshop on Policy-Based Autonomic Data Governance (PADG), 3–20. (2018)
  71. Cussens, J., & Russo, A.
    Preface to the Special Issue on Inductive Logic Programming. Mach. Learn., 107(7), 1095–1096. (2018)
  72. Law, M.
    Inductive Learning of Answer Set Programs [PhD thesis, Imperial College London]. (2018)
  73. Law, M., Russo, A., & Broda, K.
    The Complexity and Generality of Learning Answer Set Programs. Artif. Intell., 259, 110–146. (2018)
  74. Wu, B., Russo, A., Law, M., & Inoue, K.
    Learning Commonsense Knowledge through Interactive Dialogue. Technical Communications of the 34th International Conference on Logic Programming (ICLP), 12:1–12:19. (2018)
  75. Bertino, E., de Mel, G., Russo, A., Calo, S. B., & Verma, D. C.
    Community-Based Self Generation of Policies and Processes for Assets: Concepts and Research Directions. Proceedings of the IEEE International Conference on Big Data (Big Data), 2961–2969. (2017)
  76. Chabierski, P., Russo, A., Law, M., & Broda, K.
    Machine Comprehension of Text Using Combinatory Categorial Grammar and Answer Set Programs. Proceedings of the 13th International Symposium on Commonsense Reasoning (COMMONSENSE). (2017)
  77. Gomoluch, P., Alrajeh, D., Russo, A., & Bucchiarone, A.
    Towards learning domain-independent planning heuristics. Workshop on Architectures for Generality and Autonomy (AGA) at the 26th International Joint Conference on Artificial Intelligence (IJCAI). (2017)
  78. Rafiq, Y., Dickens, L., Russo, A., Bandara, A. K., Yang, M., Stuart, A., Levine, M., Calikli, G., Price, B. A., & Nuseibeh, B.
    Learning to Share: Engineering Adaptive Decision-Support for Online Social Networks. Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE), 280–285. (2017)
  79. Rankothge, W., Le, F., Russo, A., & Lobo, J.
    Optimizing Resource Allocation for Virtualized Network Functions in a Cloud Center Using Genetic Algorithms. IEEE Trans Netw Serv Manag, 14(2), 343–356. (2017)
  80. Alrajeh, D., Russo, A., Uchitel, S., & Kramer, J.
    Logic-Based Learning in Software Engineering. Proceedings of the 38th International Conference on Software Engineering (ICSE), 892–893. (2016)
  81. Alrajeh, D., van Lamsweerde, A., Kramer, J., Russo, A., & Uchitel, S.
    Risk-Driven Revision of Requirements Models. Proceedings of the 38th International Conference on Software Engineering (ICSE), 855–865. (2016)
  82. Bikakis, A., Caire, P., Clark, K., Cornelius, G., Ma, J., Miller, R., Russo, A., & Voos, H.
    Collaborative Explanation and Response in Assisted Living Environments Enhanced with Humanoid Robots. Proceedings of the 8th International Conference on Agents and Artificial Intelligence (ICAART), 506–511. (2016)
  83. Deane, G.
    Preferential Description Logics: Reasoning in the presence of inconsistencies [PhD thesis, Imperial College London]. (2016)
  84. Dragiev, S., Russo, A., Broda, K., Law, M., & Turliuc, C.-R.
    An Abductive-Inductive Algorithm for Probabilistic Inductive Logic Programming. Proceedings of the 26th International Conference on Inductive Logic Programming (ILP), 20–26. (2016)
  85. Law, M., Russo, A., & Broda, K.
    Iterative Learning of Answer Set Programs from Context Dependent Examples. Theory Pract. Log. Program., 16(5-6), 834–848. (2016)
  86. Ma, J., Le, F., Russo, A., & Lobo, J.
    Declarative Framework for Specification, Simulation and Analysis of Distributed Applications. IEEE Trans. Knowl. Data Eng., 28(6), 1489–1502. (2016)
  87. Turliuc, C.-R., Dickens, L., Russo, A., & Broda, K.
    Probabilistic Abductive Logic Programming Using Dirichlet Priors. Int. J. Approx. Reason., 78, 223–240. (2016)
  88. Al-Negheimish, H., & Russo, A.
    Reduction of ILP Search Space with Bottom-up Propositionalisation. Proceedings of the 26th International Conference on Inductive Logic Programming (ILP), 1–7. (2016)
  89. Çalikli, G., Law, M., Bandara, A. K., Russo, A., Dickens, L., Price, B. A., Stuart, A., Levine, M., & Nuseibeh, B.
    Privacy Dynamics: Learning Privacy Norms for Social Software. Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), 47–56. (2016)
  90. Alrajeh, D., Kramer, J., Russo, A., & Uchitel, S.
    Automated Support for Diagnosis and Repair. Commun. ACM, 58(2), 65–72. (2015)
  91. Athakravi, D.
    Inductive Logic Programming Using Bounded Hypothesis Space [PhD thesis, Imperial College London]. (2015)
  92. Athakravi, D., Satoh, K., Law, M., Broda, K., & Russo, A.
    Automated Inference of Rules with Exception from Past Legal Cases Using ASP. Proceedings of the 13th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), 83–96. (2015)
  93. Bucchiarone, A., Dulay, N., Lavygina, A., Marconi, A., Raik, H., & Russo, A.
    An Approach for Collective Adaptation in Socio-Technical Systems. IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, 43–48. (2015)
  94. Deane, G., Broda, K., & Russo, A.
    Reasoning in the Presence of Inconsistency through Preferential ALC. Proceedings of the 20th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR), 67–80. (2015)
  95. Lavygina, A., Russo, A., & Dulay, N.
    Integrating Privacy and Safety Criteria into Planning Tasks. Proceedings of the 11th International Workshop on Security and Trust Management (STM), 20–36. (2015)
  96. Law, M., Russo, A., & Broda, K.
    Learning Weak Constraints in Answer Set Programming. Theory Pract. Log. Program., 15(4-5), 511–525. (2015)
  97. Ma, J., Le, F., Russo, A., & Lobo, J.
    Detecting Distributed Signature-Based Intrusion: The Case of Multi-Path Routing Attacks. Proceedings of the IEEE Conference on Computer Communications (INFOCOM), 558–566. (2015)
  98. Rankothge, W., Le, F., Russo, A., & Lobo, J.
    Experimental Results on the Use of Genetic Algorithms for Scaling Virtualized Network Functions. IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 47–53. (2015)
  99. Rankothge, W., Ma, J., Le, F., Russo, A., & Lobo, J.
    Towards Making Network Function Virtualization a Cloud Computing Service. Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management (IM), 89–97. (2015)
  100. Turliuc, C.-R., Dickens, L., Russo, A., & Broda, K.
    Probabilistic Abductive Logic Programming Using Dirichlet Priors. Workshop on Probabilistic Logic Programming (PLP) at the 31st International Conference on Logic Programming (ICLP), 85–98. (2015)
  101. Athakravi, D., Alrajeh, D., Broda, K., Russo, A., & Satoh, K.
    Inductive Learning Using Constraint-Driven Bias. Proceedings of the 24th International Conference on Inductive Logic Programming (ILP), 16–32. (2014)
  102. Law, M., Russo, A., & Broda, K.
    Inductive Learning of Answer Set Programs. Proceedings of the 14th European Conference on Logics in Artificial Intelligence (JELIA), 311–325. (2014)
  103. Smith, J., Lavygina, A., Ma, J., Russo, A., & Dulay, N.
    Learning to Recognise Disruptive Smartphone Notifications. Proceedings of the 16th International Conference on Human-Computer Interaction with Mobile Devices & Services (MobileHCI), 121–124. (2014)
  104. Smith, J., Lavygina, A., Russo, A., & Dulay, N.
    When Did Your Smartphone Bother You Last? Proceedings of the ACM Conference on Ubiquitous Computing (UbiComp), 409–414. (2014)
  105. Alrajeh, D., Kramer, J., Russo, A., & Uchitel, S.
    Elaborating Requirements Using Model Checking and Inductive Learning. IEEE Trans. Softw. Eng., 39(3), 361–383. (2013)
  106. Alrajeh, D., Miller, R., Russo, A., & Uchitel, S.
    Reasoning about Triggered Scenarios in Logic Programming. Theory Pract. Log. Program., 13(4-5-Online-Supplement). (2013)
  107. Alrajeh, D., Russo, A., Lockerbie, J., Maiden, N. A. M., Mavin, A., & Novak, M.
    Computational Alignment of Goals and Scenarios for Complex Systems. Proceedings of the 35th International Conference on Software Engineering (ICSE), 1249–1252. (2013)
  108. Athakravi, D., Corapi, D., Broda, K., & Russo, A.
    Learning through Hypothesis Refinement Using Answer Set Programming. Proceedings of the 23rd International Conference on Inductive Logic Programming (ILP), 31–46. (2013)
  109. Ma, J., Le, F., Wood, D., Russo, A., & Lobo, J.
    A Declarative Approach to Distributed Computing: Specification, Execution and Analysis. Theory Pract. Log. Program., 13(4-5), 815–830. (2013)
  110. Sykes, D., Corapi, D., Magee, J., Kramer, J., Russo, A., & Inoue, K.
    Learning Revised Models for Planning in Adaptive Systems. Proceedings of the 35th International Conference on Software Engineering (ICSE), 63–71. (2013)
  111. Turliuc, C.-R., Maimari, N., Russo, A., & Broda, K.
    On Minimality and Integrity Constraints in Probabilistic Abduction. Proceedings of the 19th International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR), 759–775. (2013)
  112. Uchitel, S., Alrajeh, D., Ben-David, S., Braberman, V. A., Chechik, M., de Caso, G., D’Ippolito, N., Fischbein, D., Garbervetsky, D., Kramer, J., Russo, A., & Sibay, G. E.
    Supporting Incremental Behaviour Model Elaboration. Comput Sci Res Dev, 28(4), 279–293. (2013)
  113. Alrajeh, D., Kramer, J., Russo, A., & Uchitel, S.
    Learning from Vacuously Satisfiable Scenario-Based Specifications. Proceedings of the 15th International Conference on Fundamental Approaches to Software Engineering (FASE), 377–393. (2012)
  114. Alrajeh, D., Kramer, J., van Lamsweerde, A., Russo, A., & Uchitel, S.
    Generating Obstacle Conditions for Requirements Completeness. Proceedings of the 34th International Conference on Software Engineering (ICSE), 705–715. (2012)
  115. Athakravi, D., Broda, K., & Russo, A.
    Predicate Invention in Inductive Logic Programming. Imperial College Computing Student Workshop (ICCSW), 15–21. (2012)
  116. Athakravi, D., Corapi, D., Russo, A., Vos, M. D., Padget, J. A., & Satoh, K.
    Handling Change in Normative Specifications. Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1369–1370. (2012)
  117. Becker, M. Y., Russo, A., & Sultana, N.
    Foundations of Logic-Based Trust Management. IEEE Symposium on Security and Privacy (SP), 161–175. (2012)
  118. Dickens, L., Molloy, I., Lobo, J., Cheng, P.-C., & Russo, A.
    Learning Stochastic Models of Information Flow. Proceedings of the IEEE 28th International Conference on Data Engineering (ICDE), 570–581. (2012)
  119. Lobo, J., Ma, J., Russo, A., & Le, F.
    Declarative Distributed Computing. In Correct Reasoning - Essays on Logic-Based AI in Honour of Vladimir Lifschitz (pp. 454–470). Springer. (2012)
  120. Molloy, I., Dickens, L., Morisset, C., Cheng, P.-C., Lobo, J., & Russo, A.
    Risk-Based Security Decisions under Uncertainty. Proceedings of the 2nd ACM Conference on Data and Application Security and Privacy (CODASPY), 157–168. (2012)
  121. Alrajeh, D., Kramer, J., Russo, A., & Uchitel, S.
    An Inductive Approach for Modal Transition System Refinement. Technical Communications of the 27th International Conference on Logic Programming (ICLP), 106–116. (2011)
  122. Alrajeh, D., Russo, A., Uchitel, S., & Kramer, J.
    Integrating Model Checking and Inductive Logic Programming. Proceedings of the 21st International Conference on Inductive Logic Programming (ILP), 45–60. (2011)
  123. Corapi, D.
    Nonmonotonic Inductive Logic Programming as Abductive Search [PhD thesis, Imperial College London]. (2011)
  124. Corapi, D., Russo, A., & Lupu, E.
    Inductive Logic Programming in Answer Set Programming. Proceedings of the 21st International Conference on Inductive Logic Programming (ILP), 91–97. (2011)
  125. Corapi, D., Sykes, D., Inoue, K., & Russo, A.
    Probabilistic Rule Learning in Nonmonotonic Domains. International Workshop on Computational Logic in Multi-Agent Systems (CLIMA), 243–258. (2011)
  126. Craven, R., Lobo, J., Lupu, E., Russo, A., & Sloman, M.
    Policy Refinement: Decomposition and Operationalization for Dynamic Domains. Proceedings of the 7th International Conference on Network and Service Management (CNSM), 1–9. (2011)
  127. Kimber, T.
    Learning Definite and Normal Logic Programs by Induction on Failure [PhD thesis, Imperial College London]. (2011)
  128. Lobo, J., Ma, J., Russo, A., Lupu, E., Calo, S. B., & Sloman, M.
    Refinement of History-Based Policies. In Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning - Essays Dedicated to Michael Gelfond on the Occasion of His 65th Birthday (pp. 280–299). Springer. (2011)
  129. Ma, J.
    Distributed Abductive Reasoning: Theory, Implementation and Application [PhD thesis, Imperial College London]. (2011)
  130. Ma, J., Russo, A., Broda, K., & Lupu, E.
    Multi-Agent Abductive Reasoning with Confidentiality. Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1137–1138. (2011)
  131. Markitanis, A., Corapi, D., Russo, A., & Lupu, E. C.
    Learning User Behaviours in Real Mobile Domains. Latest Advances in Inductive Logic Programming (ILP), 43–51. (2011)
  132. Alrajeh, D., Kramer, J., Russo, A., & Uchitel, S.
    Deriving Non-Zeno Behaviour Models from Goal Models Using ILP. Form. Asp. Comput, 22(3-4), 217–241. (2010)
  133. Casale, S., Russo, A., & Serrano, S.
    Analysis of Robustness of Attributes Selection Applied to Speech Emotion Recognition. Proceedings of the 18th European Signal Processing Conference (EUSIPCO), 1174–1178. (2010)
  134. Corapi, D., Russo, A., & Lupu, E.
    Inductive Logic Programming as Abductive Search. Technical Communications of the 26th International Conference on Logic Programming (ICLP), 54–63. (2010)
  135. Corapi, D., Vos, M. D., Padget, J. A., Russo, A., & Satoh, K.
    Norm Refinement and Design through Inductive Learning. International Workshop on Coordination, Organizations, Institutions, and Norms in Agent Systems (COIN), 77–94. (2010)
  136. Craven, R., Lobo, J., Lupu, E. C., Russo, A., & Sloman, M.
    Decomposition Techniques for Policy Refinement. Proceedings of the 6th International Conference on Network and Service Management (CNSM), 72–79. (2010)
  137. Dickens, L., Broda, K., & Russo, A.
    The Dynamics of Multi-Agent Reinforcement Learning. Proceedings of the 19th European Conference on Artificial Intelligence (ECAI), 367–372. (2010)
  138. Gabbay, D. M., Rodrigues, O., & Russo, A.
    Revision, Acceptability and Context - Theoretical and Algorithmic Aspects. Springer. (2010)
  139. Hosobe, H., Satoh, K., Ma, J., Russo, A., & Broda, K.
    Speculative Constraint Processing for Hierarchical Agents. AI Commun. Eur. J. Artif. Intell., 23(4), 373–388. (2010)
  140. Ma, J., Broda, K., Goebel, R., Hosobe, H., Russo, A., & Satoh, K.
    Speculative Abductive Reasoning for Hierarchical Agent Systems. International Workshop on Computational Logic in Multi-Agent Systems (CLIMA), 49–64. (2010)
  141. Ma, J., Broda, K., Russo, A., & Lupu, E.
    Distributed Abductive Reasoning with Constraints. International Workshop on Declarative Agent Languages and Technologies (DALT), 148–166. (2010)
  142. Ma, J., Russo, A., Broda, K., & Lupu, E.
    Distributed Abductive Reasoning with Constraints. Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1381–1382. (2010)
  143. Maggi, F. M., Corapi, D., Russo, A., Lupu, E., & Visaggio, G.
    Revising Process Models through Inductive Learning. Business Process Management Workshops, 66, 182–193. (2010)
  144. Alrajeh, D.
    Requirements Elaboration Using Model Checking and Inductive Learning [PhD thesis]. Imperial College London. (2009)
  145. Alrajeh, D., Kramer, J., Russo, A., & Uchitel, S.
    Learning Operational Requirements from Goal Models. Proceedings of the 31st International Conference on Software Engineering (ICSE), 265–275. (2009)
  146. Alrajeh, D., Ray, O., Russo, A., & Uchitel, S.
    Using Abduction and Induction for Operational Requirements Elaboration. J. Appl. Log., 7(3), 275–288. (2009)
  147. Bandara, A. K., Kakas, A. C., Lupu, E. C., & Russo, A.
    Using Argumentation Logic for Firewall Configuration Management. Proceedings of the 11th IFIP/IEEE International Symposium on Integrated Network Management (IM), 180–187. (2009)
  148. Beritelli, F., Casale, S., Russo, A., & Serrano, S.
    Adaptive V/UV Speech Detection Based on Characterization of Background Noise. EURASIP J Audio Speech Music Process, 2009. (2009)
  149. Broda, K., Clark, K., Miller, R., & Russo, A.
    SAGE: A Logical Agent-Based Environment Monitoring and Control System. Proceedings of the European Conference on Ambient Intelligence (AmI), 112–117. (2009)
  150. Charalambides, M., Flegkas, P., Pavlou, G., Rubio-Loyola, J., Bandara, A. K., Lupu, E. C., Russo, A., Dulay, N., & Sloman, M.
    Policy Conflict Analysis for Diffserv Quality of Service Management. IEEE Trans Netw Serv Manag, 6(1), 15–30. (2009)
  151. Corapi, D., Ray, O., Russo, A., Bandara, A. K., & Lupu, E. C.
    Learning Rules from User Behaviour. Proceedings of the 5th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI), 459–468. (2009)
  152. Craven, R., Lobo, J., Lupu, E., Russo, A., & Sloman, M.
    Security Policy Refinement Using Data Integration: A Position Paper. Proceedings of the 2nd ACM Workshop on Assurable and Usable Security Configuration (SafeConfig), 25–28. (2009)
  153. Craven, R., Lobo, J., Ma, J., Russo, A., Lupu, E. C., & Bandara, A. K.
    Expressive Policy Analysis with Enhanced System Dynamicity. Proceedings of the 2009 ACM Symposium on Information, Computer and Communications Security (ASIACCS), 239–250. (2009)
  154. Dickens, L.
    Learning to Act Stochastically [PhD thesis, Imperial College London]. (2009)
  155. Kimber, T., Broda, K., & Russo, A.
    Induction on Failure: Learning Connected Horn Theories. Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), 169–181. (2009)
  156. Ma, J., Russo, A., Broda, K., Hosobe, H., & Satoh, K.
    On the Implementation of Speculative Constraint Processing. International Workshop on Computational Logic in Multi-Agent Systems (CLIMA), 178–195. (2009)
  157. Ma, J., Russo, A., Broda, K., & Lupu, E.
    Multi-Agent Planning with Confidentiality. Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1275–1276. (2009)
  158. Alrajeh, D., Russo, A., & Uchitel, S.
    Deriving Non-Zeno Behavior Models from Goal Models Using ILP. Proceedings of the 11th International Conference on Fundamental Approaches to Software Engineering (FASE), 1–15. (2008)
  159. Casale, S., Russo, A., Scebba, G., & Serrano, S.
    Speech Emotion Classification Using Machine Learning Algorithms. Proceedings of the 2th IEEE International Conference on Semantic Computing (ICSC), 158–165. (2008)
  160. Gabbay, D. M., Rodrigues, O., & Russo, A.
    Belief Revision in Non-Classical Logics. Rev. Symb. Log., 1(3), 267–304. (2008)
  161. Ma, J., Broda, K., Russo, A., & Clark, K.
    A Dynamic System for Distributed Reasoning. Proceedings of the AAAI 2008 Spring Symposium on Architectures for Intelligent Theory-Based Agents, 31–36. (2008)
  162. Ma, J., Russo, A., Broda, K., & Clark, K.
    DARE: A System for Distributed Abductive Reasoning. Auton Agents Multi Agent Syst, 16(3), 271–297. (2008)
  163. Bandara, A. K., Russo, A., & Lupu, E. C.
    Towards Learning Privacy Policies. 8th IEEE International Workshop on Policies for Distributed Systems and Networks (POLICY), 274. (2007)
  164. Casale, S., Russo, A., & Serrano, S.
    Multistyle Classification of Speech under Stress Using Feature Subset Selection Based on Genetic Algorithms. Speech Commun., 49(10-11), 801–810. (2007)
  165. Heaven, W. J. D.
    Object-Oriented Specification: Analysable Patterns and Change Management [PhD thesis]. Imperial College London. (2007)
  166. Maraviglia, G., Masi, M., Merlo, V., Licandro, F., Russo, A., & Schembra, G.
    Synchronous Multipoint E-Learning Realized on an Intelligent Software-Router Platform over Unicast Networks: Design and Performance Issues. Proceedings of 12th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 1172–1179. (2007)
  167. Alrajeh, D., Ray, O., Russo, A., & Uchitel, S.
    Extracting Requirements from Scenarios with ILP. Proceedings of the 16th International Conference on Inductive Logic Programming (ILP), 64–78. (2006)
  168. Alrajeh, D., Russo, A., & Uchitel, S.
    Inferring Operational Requirements from Scenarios and Goal Models Using Inductive Learning. Proceedings of the International Workshop on Scenarios and State Machines (SCESM): Models, Algorithms, and Tools, 29–36. (2006)
  169. Bandara, A. K., Kakas, A. C., Lupu, E. C., & Russo, A.
    Using Argumentation Logic for Firewall Policy Specification and Analysis. International Workshop on Distributed Systems: Operations and Management (DSOM), 185–196. (2006)
  170. Bandara, A. K., Lupu, E. C., Russo, A., Dulay, N., Sloman, M., Flegkas, P., Charalambides, M., & Pavlou, G.
    Policy Refinement for IP Differentiated Services Quality of Service Management. IEEE Trans Netw Serv Manag, 3(2), 2–13. (2006)
  171. Casale, S., Russo, A., & Serrano, S.
    Classification of Speech under Stress Using Features Selected by Genetic Algorithms. Proceedings of the 14th European Signal Processing Conference (EUSIPCO), 1–5. (2006)
  172. Charalambides, M., Flegkas, P., Pavlou, G., Rubio-Loyola, J., Bandara, A. K., Lupu, E. C., Russo, A., Sloman, M., & Dulay, N.
    Dynamic Policy Analysis and Conflict Resolution for DiffServ Quality of Service Management. Proceedings of the 10th IEEE/IFIP Network Operations and Management Symposium (NOMS), 294–304. (2006)
  173. Bandara, A. K.
    A Formal Approach to Analysis and Refinement of Policies [PhD thesis]. Imperial College London. (2005)
  174. Bandara, A. K., Lupu, E. C., Russo, A., Dulay, N., Sloman, M., Flegkas, P., Charalambides, M., & Pavlou, G.
    Policy Refinement for DiffServ Quality of Service Management. Proceedings of the 9th IFIP/IEEE International Symposium on Integrated Network Management (IM), 469–482. (2005)
  175. Broda, K., & Russo, A.
    Compiled Labelled Deductive Systems for Access Control. In We Will Show Them: Essays in Honour of Dov Gabbay (pp. 309–338). College Publications. (2005)
  176. Charalambides, M., Flegkas, P., Pavlou, G., Bandara, A. K., Lupu, E. C., Russo, A., Dulay, N., Sloman, M., & Rubio-Loyola, J.
    Policy Conflict Analysis for Quality of Service Management. 6th IEEE International Workshop on Policies for Distributed Systems and Networks (POLICY), 99–108. (2005)
  177. Heaven, W., & Russo, A.
    Enhancing the Alloy Analyzer with Patterns of Analysis. Proceedings of the 15th International Workshop on Logic Programming Environments, 14–30. (2005)
  178. Ray, O.
    Hybrid Abductive Inductive Learning [PhD thesis]. Imperial College London. (2005)
  179. Bandara, A. K., Lupu, E., Moffett, J. D., & Russo, A.
    A Goal-Based Approach to Policy Refinement. 5th IEEE International Workshop on Policies for Distributed Systems and Networks (POLICY), 229–239. (2004)
  180. Ray, O., Broda, K., & Russo, A.
    Generalised Kernel Sets for Inverse Entailment. Proceedings of the 20th International Conference on Logic Programming (ICLP), 165–179. (2004)
  181. Rodrigues, O., d’Avila Garcez, A. S., & Russo, A.
    Reasoning about Requirements Evolution Using Clustered Belief Revision. Proceedings of the 17th Brazilian Symposium on Artificial Intelligence (SBIA), 41–51. (2004)
  182. Bandara, A. K., Lupu, E., & Russo, A.
    Using Event Calculus to Formalise Policy Specification and Analysis. 4th IEEE International Workshop on Policies for Distributed Systems and Networks (POLICY), 26–39. (2003)
  183. Ray, O., Broda, K., & Russo, A.
    Hybrid Abductive Inductive Learning: A Generalisation of Progol. Proceedings of the 13th International Conference (ILP), 311–328. (2003)
  184. d’Avila Garcez, A. S., Russo, A., Nuseibeh, B., & Kramer, J.
    Combining Abductive Reasoning and Inductive Learning to Evolve Requirements Specifications. IEE Proc Softw, 150(1), 25–38. (2003)
  185. Broda, K., Gabbay, D. M., Lamb, L. C., & Russo, A.
    Labelled Natural Deduction for Conditional Logics of Normality. Log. J. IGPL Interest Group Pure Appl. Log., 10(2), 123–163. (2002)
  186. Russo, A., Miller, R., Nuseibeh, B., & Kramer, J.
    An Abductive Approach for Analysing Event-Based Requirements Specifications. Proceedings of the 18th International Conference on Logic Programming (ICLP), 22–37. (2002)
  187. Nuseibeh, B., Easterbrook, S. M., & Russo, A.
    Making Inconsistency Respectable in Software Development. J Syst Softw, 58(2), 171–180. (2001)
  188. d’Avila Garcez, A. S., Russo, A., Nuseibeh, B., & Kramer, J.
    An Analysis-Revision Cycle to Evolve Requirements Specifications. Proceedings of the 16th IEEE International Conference on Automated Software Engineering (ASE), 354–358. (2001)
  189. Nuseibeh, B., Easterbrook, S. M., & Russo, A.
    Leveraging Inconsistency in Software Development. Computer, 33(4), 24–29. (2000)
  190. Broda, K., Finger, M., & Russo, A.
    Labelled Natural Deduction for Substructural Logics. Log. J. IGPL Interest Group Pure Appl. Log., 7(3), 283–318. (1999)
  191. Nuseibeh, B., & Russo, A.
    Using Abduction to Evolve Inconsistent Requirements Specification. Australas J Inf Syst, 6(2). (1999)
  192. Russo, A., Nuseibeh, B., & Kramer, J.
    Restructuring Requirement Specifications. IEE Proc Softw, 146(1), 44–50. (1999)
  193. Russo, A., Nuseibeh, B., & Kramer, J.
    Restructuring Requirements Specifications for Managing Inconsistency and Change: A Case Study. Proceedings of the 3rd International Conference on Requirements Engineering (ICRE), 51–60. (1998)
  194. D’Agostino, M., Gabbay, D. M., & Russo, A.
    Grafting Modalities onto Substructural Implication Systems. Stud Logica, 59(1), 65–102. (1997)
  195. Russo, A.
    Generalising Propositional Modal Logic Using Labelled Deductive Systems. Proceedings of the International Workshop on Frontiers of Combining Systems (FroCoS), 57–73. (1996)
  196. de Rosis, F., Pizzutilo, S., Russo, A., Berry, D. C., & Molina, F. J. N.
    Modeling the User Knowledge by Belief Networks. User Model User Adapt Interact, 2(4), 367–388. (1992)