Michael Katz  Michael Katz photo         

contact information

Principal Research Staff Member
Thomas J. Watson Research Center, Yorktown Heights, NY USA
  

links

Professional Associations

Professional Associations:  Association for the Advancement of Artificial Intelligence (AAAI)


Software

The page includes links to the open-sourced software I was partially responsible for developing.

IBM Research AI Planning Service (DockerHub Image)

K* search implementation of a Top-K planner (DockerHub Image)

Cerberus planner, post-IPC 2018 version (DockerHub Image)

Forbid-Iterative (FI) Planner suite for top-k, top-quality, and diverse computational tasks (DockerHub Image)

Diversity score computation for a set of plans (DockerHub Image)

 

Data

IPC: A Graph Data Set Compiled from International Planning Competitions

IPC: An IMAGE Data Set Compiled from International Planning Competitions

PDDL domain inspired by risk management problem

PDDL benchmark generated from Data Science grammar

PDDL instances of structurally restricted planning tasks

 

Competitions

I have participated in the deterministic part of the IPC-2018 - International Planning Competition 2018
with multiple planners. One of them, Delfi has won the sequential optimal track. The source code for Delfi can be found here.

Other planners from IPC2018 include

 

[1] M. Katz, N. Lipovetzky, D. Moshkovich, A. Tuisov, Adapting Novelty to Classical Planning as Heuristic Search, in Proceedings of The International Conference on Automated Planning and Scheduling (ICAPS), Pittsburgh, PA, USA, 2017.

[2] M. Katz, Red-Black Heuristics for Planning Tasks with Conditional Effects, in Proceedings of The 33rd AAAI Conference on Artificial Intelligence (AAAI), Honolulu, HI, USA, 2019.



I have participated in the deterministic part of the IPC-2014 - International Planning Competition 2014
with two planners, Mercury for the sequential satisficing track and Metis for the sequential optimal track.
Mercury (with Joerg Hoffmann) has won two awards:

  • Runner-Up in the sequential satisficing track, and
  • Innovative Planner Award.


The source code for the planners can be found here (or by request):



More details on Mercury:

Mercury is a classical planner - a solver for classical (deterministic) planning tasks specified in PDDL 3.1.

It is an open source planner, built on top of the Fast Downward planning system. The source code is available here.

Running the planner:

  • To build the planner run ./build
  • To run the planner use ./plan <DOMAIN> <PROBLEM> <PLAN_FILE>

PDDL examples can be found at https://bitbucket.org/aibasel/downward-benchmarks

 

Mercury has won two awards at the 2014 International Planning Competition:

  1. Runner-up of the Deterministic Sequential Track 
  2. Innovative Planner Award

Papers related to Mercury: