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BIFROST Version 0.7

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November 05, 2007, at 08:21 PM by Rune -
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(ps,pdf,bib) Fault Tolerant Planning: Moving Toward Probabilistic Uncertainty Models in Symbolic Non-Deterministic Planning, R.M. Jensen, R.E. Bryant, and M.M. Veloso, Submitted to JAIR, 2004

(ps,pdf,bib) State-Set Branching: Leveraging OBDDs for Heuristic Search, R.M. Jensen, R.E. Bryant, and M.M. Veloso, Submitted to AIJ, 2004

(ps,pdf,bib) Fault Tolerant Planning: Toward Probabilistic Uncertainty Models in Symbolic Non-Deterministic Planning, R.M. Jensen, M.M. Veloso, and R.E. Bryant, In Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS-04), 2004.

(ps,pdf,bib) Guided Symbolic Universal Planning, R.M. Jensen, M.M. Veloso, and R.E. Bryant, Proceedings of the 13th International Conference on Automated Planning and Scheduling (ICAPS-03), pages 123-132, Trento, Italy, 2003.

(ps,pdf,bib) SetA*: An efficient BDD-Based Heuristic Search Algorithm, R.M. Jensen, R.E. Bryant and M.M. Veloso, In Proceedings of 18th National Conference on Artificial Intelligence (AAAI'02), pages 668-673, 2002.

(ps,pdf,bib) OBDD-Based Optimistic and Strong Cyclic Adversarial Planning, R.M. Jensen, M.M. Veloso and M.H. Bowling, In Proceedings of the 6th European Conference on Planning (ECP-01), Springer-Verlag.

to:
  • Synthesis of Fault Tolerant Plans for Non-Deterministic Domains, R.M. Jensen, M.M. Veloso and R.E. Bryant, ICAPS'03 Workshop on Planning under Uncertainty and Incomplete Information, 2003.
  • State-set branching: Leveraging BDDs for heuristic search, R.M. Jensen, R.E. Bryant, and M.M. Veloso, In Press.
  • Fault Tolerant Planning: Toward Probabilistic Uncertainty Models in Symbolic Non-Deterministic Planning, R.M. Jensen, M.M. Veloso, and R.E. Bryant, In Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS-04), 2004.
  • Guided Symbolic Universal Planning, R.M. Jensen, M.M. Veloso, and R.E. Bryant, Proceedings of the 13th International Conference on Automated Planning and Scheduling (ICAPS-03), pages 123-132, Trento, Italy, 2003.
  • SetA*: An efficient BDD-Based Heuristic Search Algorithm, R.M. Jensen, R.E. Bryant and M.M. Veloso, In Proceedings of 18th National Conference on Artificial Intelligence (AAAI'02), pages 668-673, 2002.
  • OBDD-Based Optimistic and Strong Cyclic Adversarial Planning, R.M. Jensen, M.M. Veloso and M.H. Bowling, In Proceedings of the 6th European Conference on Planning (ECP-01), Springer-Verlag.
November 05, 2007, at 08:16 PM by Rune -
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(:Tittle BIFROST Version 0.7:)

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(:Title BIFROST Version 0.7:)

November 05, 2007, at 08:16 PM by Rune -
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  • [[http://www.itu.dk/people/rmj/data/systems/bifrost07/buddy20.tar.gz | buddy20.tar.gz unmodified version (0.4 MB).
to:
  • buddy20.tar.gz unmodified version (0.4 MB).
November 05, 2007, at 08:16 PM by Rune -
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(:Tittle BIFROST Version 0.7:)

The Bdd-based InFoRmed planning and cOntroller Synthesis Tool (BIFROST) is a BDD-based search engine for deterministic and non-deterministic planning/search/control domains. It takes problems written in either NADL (Jensen & Veloso, AIPS2000 and JAIR 1999) or PDDL. It has 11 algorithms for deterministic domains including blind forward, backward, bidirectional, SetA*, and BDDA* (with a range of different heuristics). It has 10 algorithms for non-deterministic domains including the classical weak, strong cyclic, and strong in blind and guided versions (ICAPS-03), and adversarial weak and strong cyclic. In addition, BIFROST includes various algorithms for fault tolerant planning.

This code is precompiled for Linux RedHat 7.1. It should be fairly easy to port to other OSs. First download BIFROST 0.7 and the modifed BuDDy BDD package used by BIFROST 0.7. You can also download the unmodified package and uncomment the special functions.

  • bifrost07.tar.gz (5.5 MB).
  • buddy20split.tar.gz modified version (1.1 MB).
  • [[http://www.itu.dk/people/rmj/data/systems/bifrost07/buddy20.tar.gz | buddy20.tar.gz unmodified version (0.4 MB).

Unpack in the usual way: "gunzip bifrost07.tar.gz", "tar xvf bifrost07.tar", "gunzip buddy20split.tar.gz", "tar xvf buddy20split.tar". If you believe things should work without re-compilation then simply run "0.7/bifrost -h" to see the options. Take a look at "main.cc" to see what goes on under the hood. I strongly suggest that you write email to me about the particular experiment you are going to perform. Your computations will not say much if e.g. the BDD package is intialized with too small caches for what you had in mind.

For a complete recompilation, start with the buddy package in its main directory run make clean, make all. After successful compilation, your library is sitting in "src". After that open the "Makefile" in "0.7" and edit the library link to fit your system. Then do a "make clean" and "make all". If the "LEX" and "YACC" are giving problems, follow the instructions at the end of the make file.

BIFROST Experimental Domains

This file contains a large collection of domains used for experiments with UMOP and BIFROST. Again, I suggest you to contact me regarding particular experiments and domains. Also, don't be surpriced to find groceries shopping lists and other personal stuff here.

benchmarks.tar.gz (24.6 MB).

BIFROST related Publications

(ps,pdf,bib) Fault Tolerant Planning: Moving Toward Probabilistic Uncertainty Models in Symbolic Non-Deterministic Planning, R.M. Jensen, R.E. Bryant, and M.M. Veloso, Submitted to JAIR, 2004

(ps,pdf,bib) State-Set Branching: Leveraging OBDDs for Heuristic Search, R.M. Jensen, R.E. Bryant, and M.M. Veloso, Submitted to AIJ, 2004

(ps,pdf,bib) Fault Tolerant Planning: Toward Probabilistic Uncertainty Models in Symbolic Non-Deterministic Planning, R.M. Jensen, M.M. Veloso, and R.E. Bryant, In Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS-04), 2004.

(ps,pdf,bib) Guided Symbolic Universal Planning, R.M. Jensen, M.M. Veloso, and R.E. Bryant, Proceedings of the 13th International Conference on Automated Planning and Scheduling (ICAPS-03), pages 123-132, Trento, Italy, 2003.

(ps,pdf,bib) SetA*: An efficient BDD-Based Heuristic Search Algorithm, R.M. Jensen, R.E. Bryant and M.M. Veloso, In Proceedings of 18th National Conference on Artificial Intelligence (AAAI'02), pages 668-673, 2002.

(ps,pdf,bib) OBDD-Based Optimistic and Strong Cyclic Adversarial Planning, R.M. Jensen, M.M. Veloso and M.H. Bowling, In Proceedings of the 6th European Conference on Planning (ECP-01), Springer-Verlag.

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