Dynamic Planning, Optimisation and Learning Project

The DPOLP Project (2004-2008) was a four way collaboration between DSTO, NICTA/ANU, the University of Adelaide and the University of South Australia. The project focused on fundamental and applied research into operations/project level planning. It produced several state of the art planners dealing with uncertainty and time, and made a number of significant contributions to bridging the gap between planning/heuristic search in artificial intelligence, petri nets analysis, and statistical machine learning.

Project Members | Research | Software | Publications

Project Members

  • Douglas Aberdeen, NICTA/ANU
  • Jonathan Billington, UNISA
  • Olivier Buffet, NICTA/ANU
  • Alfredo Gabaldo, NICTA/UNSW
  • Guy Gallasch, DSTO/UNISA
  • Karyn I'Anson, DSTO
  • Owen Thomas, NICTA
  • Patrik Haslum, NICTA/ANU
  • Sarah Hickmott, UofA/NICTA
  • Melissa Liew, UofA/NICTA
  • Iain Little, ANU/NICTA
  • Brice Mitchell, DSTO
  • Sanjeev Naguleswaran, UofA
  • Jussi Rintanen, NICTA/ANU
  • Scott Sanner, NICTA/ANU
  • Sylvie Thiebaux, ANU/NICTA
  • Lewis Warren, DSTO
  • Lang White, UofA
  • Lin Zhang, DSTO


Operations planning involves larges groups of people choosing and co-ordinating tasks to produce a smoothly orchestrated operation. Automatically developing robust plans with hundreds of tasks is hard. Planning becomes even harder when trying to take the uncertainty of the world into account. NICTA, the Defence Science Technology Organisation (DSTO), the University of Adelaide, and the University of South Australia are developing theoretical frameworks, algorithms and tools that formalise, abstract, and solve such planning problems.

Research in the project explores a wide cross section of methods previously used in planning, including Markov decision processes, ML methods which would now be called "deep learning", SAT and logic based planning, planning graphs and search, Petri-net unfolding, and optimisation methods.

Software that automatically plans and schedules a set of tasks has been developed. Contributions include four planning servers to support military planning tools developed by DSTO. A further two planners received prizes at the 2006 International Probabilistic Planning Competition.

Applications of methods emerging from the project are of interest to the broader planning community, operations researchers, control theorists, and the day-to-day project managers who would like to know how a 50% chance of an adverse event could affect their project budget. DPOLP work is also becoming concerned with the presentation of planning information, including theoretical work in how to measure the similarity of plans, and how to present qualitatively different plans to the user from a spectrum of valid plans. Beyond traditional operations and project planning, DPOLP tools for the analysis of uncertainty contribute to the decision support and business planning domains.



Publications by NICTA/ANU members of the project: Conference tutorials and invited talks:
This document is maintained by Sylvie Thiebaux
Last Modified April 2016