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. Blom, M.; Pearce, AR.; Stuckey, PJ. Short-term planning for open pit mines: a review. International Journal of Mining, Reclamation and Environment. TAYLOR & FRANCIS LTD. 2019, Vol. 33, Issue 5, pp. 318-339. DOI: 10.1080/17480930.2018.1448248
  2. 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.
  3. Ramirez, M.; Papasimeon, M.; Lipovetzky, N.; Benke, L.; Miller, T.; Pearce, AR.; Scala, E.; Zamani, M. Integrated Hybrid Planning and Programmed Control for Real–Time UAV Maneuvering. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS. International Foundation for Autonomous Agents and Multiagent Systems. 2018, Vol. 2, pp. 1318-1326.
  4. Blom, M.; Shekh, S.; Gossink, D.; Miller, T.; Pearce, AR. Inventory routing for defense: Moving supplies in adversarial and partially observable environments. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology. SAGE Publications. 2018, pp. 154851291879805-154851291879805. DOI: 10.1177/1548512918798056
  5. 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
  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 Javega, M.; Papasimeon, M.; Benke, L.; Lipovetzky, N.; Miller, T.; Pearce, A. Real-Time UAV Maneuvering via Automated Planning in Simulations. IJCAI International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2017, pp. 5248-5255.
  8. Blom, M.; Pearce, AR.; Stuckey, PJ. Short-term scheduling of an open-pit mine with multiple objectives. CONSTRAINT PROGRAMMING 2015 (POSTER). TAYLOR & FRANCIS LTD. 2017, Vol. 49, Issue 5, pp. 777-795. DOI: 10.1080/0305215X.2016.1218002
  9. Miller, T.; Felli, P.; Muise, C.; Pearce, AR.; Sonenberg, L. 'Knowing Whether' in Proper Epistemic Knowledge Bases. 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI Press. 2016, pp. 1044-1055.
  10. Blom, M.; Pearce, A.; Stuckey, P. A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks over Multiple Time Periods. Management Science. INFORMS (Institute for Operations Research and Management Sciences). 2016, Vol. 62, Issue 10, pp. 3059-3084. DOI: 10.1287/mnsc.2015.2284
  11. Muise, C.; Felli, P.; Miller, T.; Pearce, AR.; Sonenberg, L. Planning for a Single Agent in a Multi-Agent Environment Using FOND. IJCAI 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. Burt, CN.; Lipovetzky, N.; Pearce, AR.; Stuckey, PJ. Approximate Uni-directional Benders Decomposition. AAAI Workshop - Technical Report. AAAI Press. 2015, Vol. WS-15-12, pp. 24-31.
  16. 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
  17. Felli, P.; Miller, T.; Muise, C.; Pearce, AR.; Sonenberg, L. Computing Social Behaviours Using Agent Models. IJCAI International Joint Conference on Artificial Intelligence. AAAI Press / International Joint Conferences on Artificial Intelligence. 2015, Vol. 2015-January, pp. 2978-2984.
  18. Muise, C.; Miller, T.; Felli, P.; Pearce, AR.; Sonenberg, L. Efficient reasoning with consistent proper epistemic knowledge bases. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS. The Association for Computing Machinery. 2015, Vol. 3, pp. 1461-1469.
  19. Davies, TO.; Pearce, AR.; Stuckey, PJ.; Sondergaard, 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.
  20. Ewin, C.; Pearce, A.; Vassos, S. Optimizing Long-Running Action Histories in the Situation Calculus Through Search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2015, Vol. LNCS 9387, pp. 85-100. DOI: 10.1007/978-3-319-25524-8_6

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