CoGNeRe is solver for probabilistic shortest path problems. Akin to other replanners like Robust-FF, CoGNeRe constructs a solution to the probabilistic problem by solving deterministic relaxations, which lets it return partial policies quickly in an online fashion. The novelty is that by using column generation, it can provide guarantees of optimality, and a lot of flexibility.

ICAPS DC Poster [pdf]

  • 2 minute talk [coming soon]
  • 6 minute talk [link]

Poster and accompanying talks for CoGNeRe at the ICAPS 2022 Doctoral Consortium.

ICAPS DC Abstract [pdf]

4 page overview of CoGNeRe, some background, and future work. Submitted as my dissertation abstract for the ICAPS 2022 Doctoral Consortium.

Short Talk [slides]

12 minute talk that gives an overview of the algorithm and what it’s trying to do. Presented at a retreat for HDR students in the ANU Intelligence Cluster.

Honours Thesis [pdf]

100 page document that gives the background, and develops the main component of the algorithm. The formulation is a bit outdated and the experiments are problematic (the version of Robust-FF that was used for testing was hand-rolled without a lot of the optimisations in the authors’ version), but the theory is good. Submitted for the research component of my Honours Degree at ANU.

Updated:

You may also enjoy