Research

• Cost-Based Query Optimization via AI Planning

  Robinson, N.; McIlraith, S. A.; and Toman, D. In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27-31, 2014, Quebec City, Quebec, Canada, 2014.

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• Query Optimization Revisited: An AI Planning Perspective

  Robinson, N.; McIlraith, S. A.; and Toman, D. In Proceedings of the ICAPS Scheduling and Planning Applications woRKshop (SPARK), June 11, Rome, Italy, 2013.

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• Advancing Planning-as-Satisfiability

  Robinson, N. PhD thesis, Griffith University and NICTA, 2012.

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• Comparing the Effectiveness of Reasoning Formalisms for Partial Models

  Saadatpanah, P.; Famelis, M.; Gorzny, J.; Robinson, N.; Chechik, M.; and Salay, R. In Proceedings of the 9th workshop on Model-Driven Engineering, Verification and Validation (MoDeVVa 2012), 2012.

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• Planning the Transformation of Network Topologies

  Yoon, Y.; Robinson, N.; Muthusamy, V.; Jacobsen, H.; and McIlraith, S. A. In Proceedings of the AAAI-12 Workshop on Problem Solving using Classical Planners (CP4PS-12), 2012.

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• Partial Weighted MaxSAT for Optimal Planning

  Robinson, N.; Gretton, C.; Pham, D. N.; and Sattar, A. In Proceedings of the 11th Pacific Rim International Conference on Artificial Intelligence, Daegu, Korea, August 30 – September 02 (Best paper award), 2010.

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• SAT-Based Parallel Planning Using a Split Representation of Actions

  Robinson, N.; Gretton, C.; Pham, D. N.; and Sattar, A. In Proceedings of the 19th International Conference on Automated Planning and Scheduling, ICAPS 2009, Thessaloniki, Greece, September 19-23, 2009.

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• A Compact and Efficient SAT Encoding for Planning

  Robinson, N.; Gretton, C.; Pham, D. N.; and Sattar, A. In Proceedings of the 18th International Conference on Automated Planning and Scheduling, ICAPS 2008, Sydney, Australia, September 14-18, 2008.

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• CO-Plan: Combining SAT-Based Planning with Forward-Search

  Robinson, N.; Gretton, C.; and Pham, D.N. In Proceedings of the 2008 International Planning Competition, IPC-6, Sydney, Australia, September, 2008.

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• Propositional Probabilistic Planning-as-Satisfiability using Stochastic Local Search

  Robinson, N.; Gretton, C.; Pham, D.N.; and Sattar, A. In Proceedings of A Reality Check for Planning and Scheduling Under Uncertainty, ICAPS workshop, Sydney, Australia, September 15, 2008.

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• LPForget: A System of Forgetting in Answer Set Programming

  Cheng, F.L.; Eiter, T.; Robinson, N.; Sattar, A.; and Wang, K. In Proceedings of AI 2006: Advances in Artificial Intelligence, 19th Australian Joint Conference on Artificial Intelligence, Hobart, Australia, December 4-8, 2006.

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• Systems and methods for responding to road changes with conditional contraction hierarchies

  Published application US20240288273A1

• Systems and methods for optimal path determination using contraction hierarchies with multi-link constraints

  US patent US12442648B2

• Systems and methods for optimal path determination using contraction hierarchies with turn costs

  US patent US12259249B2 US patent US11566909B2

• Systems and methods for optimal path determination using contraction hierarchies with link constraints

  US patent US11585668B2

• Using partitioned contraction hierarchies to determine a route from an origination point to a destination point

  US patent US11585666B2

• Conditional region-based costing in contraction hierarchies

  US patent US12320656B2

• Systems and methods for cost-based forward search based on precomputed bidirectional search

  US patent US12281905B2

• Systems and methods for generating vehicle routing directions using finite state automata

  Published application US20260063437A1

AI planning, satisfiability, routing algorithms, route optimisation and geospatial systems.