Dr Daniele Magazzeni Academics Reader in Artificial Intelligence Co-Director of Centre for Doctoral Training in Safe and Trusted AI. Research subject areas Computer science Contact details +44 020 78481587 daniele.magazzeni@kcl.ac.uk
A CASP-based approach to PDDL+ planning Balduccini, M., Magazzeni, D. & Maratea, M., 1 Jan 2016, p. 5-14. 10 p. Research output: Contribution to conference types - Paper Temporal planning as refinement-based model checking Heinz, A., Wehrle, M., Bogomolov, S., Magazzeni, D., Greitschus, M. & Podelski, A., 1 Jan 2019, Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019. Benton, J., Lipovetzky, N., Onaindia, E., Smith, D. E. & Srivastava, S. (eds.). AAAI Press, p. 195-199 5 p. (Proceedings International Conference on Automated Planning and Scheduling, ICAPS). Research output: Chapter in Book/Report/Conference proceeding - Conference paper Explainable Security Viganò, L. & Magazzeni, D., 21 Apr 2020, Proceedings of the 6th Workshop on Hot Issues in Security Principles and Trust (HotSpot 2020). 8 p. Research output: Chapter in Book/Report/Conference proceeding - Conference paper Explainable AI Planning (XAIP): Overview and the Case of Contrastive Explanation (Extended Abstract) Hoffmann, J. & Magazzeni, D., 1 Jan 2019, Reasoning Web. Explainable Artificial Intelligence - 15th International Summer School 2019, Tutorial Lectures. Krötzsch, M. & Stepanova, D. (eds.). SPRINGER, p. 277-282 6 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11810 LNCS). Research output: Chapter in Book/Report/Conference proceeding - Conference paper. DOIs: https://doi.org/10.1007/978-3-030-31423-1_9 PDDL+ Planning with temporal pattern databases Piotrowski, W., Fox, M., Long, D., Magazzeni, D. & Mercorio, F., 1 Jan 2017, WS-17-01: Artificial Intelligence and Operations Research for Social Good; WS-17-02: Artificial Intelligence, Ethics, and Society; WS-17-03: Artificial Intelligence for Connected and Automated Vehicles; WS-17-04: Artificial Intelligence for Cyber Security; WS-17-05: Artificial Intelligence for Smart Grids and Buildings; WS-17-06: Computer Poker and Imperfect Information Games; WS-17-07: Crowdsourcing, Deep Learning and Artificial Intelligence Agents; WS-17-08: Distributed Machine Learning; WS-17-09: Joint Workshop on Health Intelligence; WS-17-10: Human-Aware Artificial Intelligence; WS-17-11: Human-Machine Collaborative Learning; WS-17-12: Knowledge-Based Techniques for Problem Solving and Reasoning; WS-17-13: Plan, Activity, and Intent Recognition; WS-17-14: Symbolic Inference and Optimization; WS-17-15: What's Next for AI in Games?. AI Access Foundation, p. 930-936 7 p. (AAAI Workshop - Technical Report; vol. WS-17-01 - WS-17-15). Research output: Chapter in Book/Report/Conference proceeding - Conference paper Planning for Hybrid Systems via Satisfiability Modulo Theories Cashmore, M., Magazzeni, D. & Zehtabi, P., 2020, In : Journal Artificial Intelligence Research. 67, p. 253-283 Research output: Contribution to journal - Article. DOIs: https://doi.org/10.1613/jair.1.11751 PDDL+ planning via constraint answer set programming Balduccini, M., Magazzeni, D. & Maratea, M., 1 Jan 2016, p. 1-12. 12 p. Research output: Contribution to conference types - Paper Probabilistic Planning for Robotics with ROSPlan Canal, G., Cashmore, M., Krivić, S., Alenyà , G., Magazzeni, D. & Torras, C., 2019, Towards Autonomous Robotic Systems - 20th Annual Conference, TAROS 2019, Proceedings. Althoefer, K., Konstantinova, J. & Zhang, K. (eds.). Springer Verlag, p. 236-250 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11649 LNAI). Research output: Chapter in Book/Report/Conference proceeding - Conference paper. DOIs: https://doi.org/10.1007/978-3-030-23807-0_20 An Introduction to the Planning Domain Definition Language Haslum, P., Lipovetzky, N., Magazzeni, D. & Muise, C., 1 Jan 2019, Synthesis Lectures on Artificial Intelligence and Machine Learning: Lecture #40. 2 ed. Morgan and Claypool Publishers, p. 1-169 169 p. (Synthesis Lectures on Artificial Intelligence and Machine Learning; vol. 13, no. 2). Research output: Chapter in Book/Report/Conference proceeding - Chapter. DOIs: https://doi.org/10.2200/S00900ED2V01Y201902AIM042 Using Machine Learning for Decreasing State Uncertainty in Planning Cashmore, M., Krivic, S. & Magazzeni, D., 2019, (In preparation) In : Journal Artificial Intelligence Research. Research output: Contribution to journal - Article View all publications