Professor Adrian Pearce

  • Room: Level: 06 Room: 6.20
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Automated Planning & Scheduling
  • Optimisation in multi-agent systems and supply chains
  • Reasoning about Action and Epistemic Reasoning

Personal webpage

http://people.eng.unimelb.edu.au/adrianrp/

Biography

Professor in School of Computing and Information Systems

Researcher and innovator in planning and scheduling. My research has improved the efficiency and robustness of a range of applications including production planning for mining, supply chain optimization, robotics, logistics, air traffic management and autonomous systems.

Contributed deeply in research on reasoning about actions within the field of artificial intelligence. In conjunction with an excellent group of colleagues in the AI and Autonomy and optimisation group, we have made fundamental breakthroughs in the ability to perform collaborative planning and scheduling.

Our research group tackles optimization problems, including more efficient and productive supply chain management for agile mine scheduling.

My specialities include: Supply chain optimization, automated planning and scheduling; reasoning about action and change; optimisation in multi-agent systems; knowledge representation and reasoning; and artificial intelligence.

Recent publications

  1. Macnally, AM.; Lipovetzky, N.; Ramirez, M.; Pearce, AR. Action selection for transparent planning. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS. IFAAMAS International Foundation for Autonomous Agents and Multiagent Systems. 2018, Vol. 2, pp. 1327-1335.
  2. Ramirez, M.; Benke, L.; Papasimeon, M.; Lipovetzky, N.; Pearce, AR.; Zamani, M.; Scala, E.; Miller, T. Integrated hybrid planning and programmed control for real-time UAV maneuvering. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS. Elsevier Inc.. 2018, Vol. 2, pp. 1318-1326.
  3. Blom, M.; Shekh, S.; Gossink, D.; Miller, T.; Pearce, AR. Inventory routing for defense: Moving supplies in adversarial and partially observable environments. Journal of Defense Modeling and Simulation. 2018. DOI: 10.1177/1548512918798056
  4. Blom, M.; Pearce, AR.; Stuckey, PJ. Multi-objective short-term production scheduling for open-pit mines: a hierarchical decomposition-based algorithm. Engineering Optimization. TAYLOR & FRANCIS LTD. 2018, Vol. 50, Issue 12, pp. 2143-2160. DOI: 10.1080/0305215X.2018.1429601
  5. Blom, M.; Pearce, AR.; Stuckey, PJ. Short-term planning for open pit mines: a review. International Journal of Mining, Reclamation and Environment. 2018, pp. 1-22. DOI: 10.1080/17480930.2018.1448248
  6. Miller, T.; Pearce, AR.; Sonenberg, L. Social Planning for Trusted Autonomy. . SPRINGER INTERNATIONAL PUBLISHING AG. 2018, Vol. 117, pp. 67-86. DOI: 10.1007/978-3-319-64816-3_4
  7. Ramirez, M.; Papasimeon, M.; Benke, L.; Lipovetzky, N.; Miller, T.; Pearce, AR. Real-time UAV maneuvering via automated planning in simulations. IJCAI International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2017, pp. 5243-5245.
  8. Blom, M.; Pearce, AR.; Stuckey, PJ. Short-term scheduling of an open-pit mine with multiple objectives. Engineering Optimization. TAYLOR & FRANCIS LTD. 2017, Vol. 49, Issue 5, pp. 777-795. DOI: 10.1080/0305215X.2016.1218002
  9. Blom, ML.; Pearce, AR.; Stuckey, PJ. A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods. Management Science. INFORMS. 2016, Vol. 62, Issue 10, pp. 3059-3084. DOI: 10.1287/mnsc.2015.2284
  10. Miller, T.; Felli, P.; Muise, C.; Pearce, AR.; Sonenberg, L. Knowing Whether in proper epistemic knowledge bases. The 30th AAAI Conference on Artificial Intelligence. AAAI Press. 2016, pp. 1044-1050.
  11. Muise, C.; Felli, P.; Miller, T.; Pearce, AR.; Sonenberg, L. Planning for a single agent in a multi-agent environment using FOND. International Joint Conference On Artificial Intelligence. AAAI Press. 2016, Vol. 2016-January, pp. 3206-3212.
  12. Davies, TO.; Pearce, AR.; Stuckey, P.; Lipovetzky, N. Sequencing operator counts. IJCAI International Joint Conference on Artificial Intelligence. AAAI Press. 2016, Vol. 2016-January, pp. 4140-4144.
  13. De Giacomo, G.; Lesperance, Y.; Pearce, AR. Situation Calculus Game Structures and GDL. Frontiers in Artificial Intelligence and Applications. IOS PRESS. 2016, Vol. 285, pp. 408-416. DOI: 10.3233/978-1-61499-672-9-408
  14. Sonenberg, E.; Miller, T.; Pearce, AR.; Felli, P.; Muise, CJ.; Dignum, F. Social planning for social HRI. CoRR. arXiv.org. 2016, Vol. abs/1602.06483.
  15. Muise, C.; Dignum, F.; Felli, P.; Miller, T.; Pearce, AR.; Sonenberg, L. Towards team formation via automated planning. International Workshop on Coordination, Organisation, Institutions and Norms in Multi-Agent Systems. AAAI Press. 2016, Vol. 9628, pp. 282-299. DOI: 10.1007/978-3-319-42691-4_16
  16. Burt, CN.; Lipovetzky, N.; Pearce, AR.; Stuckey, PJ. Approximate uni-directional benders decomposition. Proceedings of PlanSOpt-15 Workshop on Planning, Search and Optimization AAAI-15 (2015). AAAI Press. 2015, Vol. WS-15-12, pp. 24-31.
  17. Kelly, RF.; Pearce, AR. Asynchronous knowledge with hidden actions in the situation calculus. Artificial Intelligence. ELSEVIER SCIENCE BV. 2015, Vol. 221, pp. 1-35. DOI: 10.1016/j.artint.2014.12.005
  18. Felli, P.; Miller, T.; Muise, C.; Pearce, AR.; Sonenberg, L. Computing Social Behaviours Using Agent Models. International Joint Conference on Artificial Intelligence, IJCAI 2015. IJCAI-INT JOINT CONF ARTIF INTELL. 2015, Vol. 2015-January, pp. 2978-2984.
  19. Muise, C.; Miller, T.; Felli, P.; Pearce, AR.; Sonenberg, L. Efficient reasoning with consistent proper epistemic knowledge bases. Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. The Association for Computing Machinery. 2015, Vol. 3, pp. 1461-1469.
  20. Davies, TO.; Pearce, AR.; Stuckey, PJ.; S√łndergaard, H. Optimisation and relaxation for multiagent planning in the situation calculus. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS. International Foundation for Autonomous Agents and Multiagent Systems. 2015, Vol. 2, pp. 1141-1149.

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile