Skip to content

Latest commit

 

History

History
555 lines (436 loc) · 23.2 KB

CHANGES.md

File metadata and controls

555 lines (436 loc) · 23.2 KB
Raw

Release notes

Fast Downward has been in development since 2003, but the current timed release model was not adopted until 2019. This file documents the changes since the first timed release, Fast Downward 19.06.

For more details, check the repository history (https://github.com/aibasel/downward) and the issue tracker (https://issues.fast-downward.org). Repository branches are named after the corresponding tracker issues.

Changes since the last release

  • option parser: We implemented a new way of defining features and parsing them from the command line. The new parser now supports defining variables for features (heuristics and landmark graphs so far) within the option string. For example let(h, lmcut(), astar(h)). This change to the parser was an important stepping stone towards solving a more general problem about how components interact. Details of the new parser are described in a blog article. While working on this, we also improved the existing documentation of enum values. https://www.fast-downward.org/ForDevelopers/Blog/TheNewOptionParser https://issues.fast-downward.org/issue1073 https://issues.fast-downward.org/issue1040

  • landmarks: Refactor the computation of preferred operators in the lmcount heuristic. The change affects configurations based on LAMA that use preferred operators. While the semantics of the code did not change, the new version is slightly faster and can solve more tasks and/or improves plan quality in an anytime configuration within the same time limit. https://issues.fast-downward.org/issue1070

Fast Downward 22.12

Released on December 15, 2022.

Highlights:

  • We now test more recent versions of Ubuntu Linux (22.04 and 20.04), macOS (11 and 12) and Python (3.8 and 3.10).

  • Most search algorithms are now faster. We fixed a performance problem related to state pruning, which also affected search configurations that did not explicitly select a pruning method.

  • All landmark factories now respect action costs. Previously, this was only the case when using admissible landmark heuristic or when using the lm_rhw landmark factory. Note that ignoring action costs (i.e., the old behaviour for landmark factories other than lm_rhw) often finds plans faster and is still possible with the adapt_costs transformation.

Details:

  • driver: Planner time is now logged in a consistent format. Previously, it would sometimes be logged in scientific notation.

  • driver, for developers: Skip pycache directory when collecting portfolios. https://issues.fast-downward.org/issue1057

  • translator: Allow importing pddl_parser without parsing arguments from command line. https://issues.fast-downward.org/issue1068

  • pruning methods: Fix a performance regression caused by spending too much time measuring elapsed time. This is now only done at verbosity level verbose or higher. Verbosity level parameter added to all pruning methods. https://issues.fast-downward.org/issue1058 Note that most search algorithms in Fast Downward always use a pruning method (a trivial method pruning nothing is used by default) and were therefore affected by this performance problem.

  • pruning methods, for developers: We cleaned up the internal structure of stubborn set pruning. https://issues.fast-downward.org/issue1059

  • landmarks: All landmark factories are now sensitive to action costs. https://issues.fast-downward.org/issue1009 When using the lmcount heuristic in inadmissible mode (option admissible=false), previously only the lm_rhw landmark factory considered action costs. Now, all landmark factories do. (This was already the case with admissible=true.) Experiments show that ignoring action costs is often beneficial when we are more interested in planner speed or coverage than plan quality. This can be achieved by using the option transform=adapt_costs(ONE).

  • landmarks: Reduce verbosity of h^m landmarks. The lm_hm landmark factory is now less verbose by default. Use verbosity level verbose or higher to enable the previous output.

  • infrastructure: Update tested OS versions and clang-tidy version. https://issues.fast-downward.org/issue1067

    • The tested Ubuntu versions are now 22.04 and 20.04.
    • The tested macOS versions are now macOS 11 and macOS 12.
    • The tested Windows version remains Windows 10.
    • We now test Python 3.10 (Ubuntu 22.04, macOS 12) and Python 3.8 (Ubuntu 20.04, macOS11, Windows 10).
    • We now use clang-tidy-12. See README.md for details.

  • infrastructure: Update delete-artifact version number in GitHub action, update zlib version in Windows build.

Fast Downward 22.06.1

Released on September 15, 2022.

This is a bugfix release fixing two serious bugs in Fast Downward 22.06:

Fast Downward 22.06

Released on June 16, 2022.

Highlights:

  • We fixed a bug in the translator component that could lead to incorrect behavior in tasks where predicates are mentioned in the goal that are not modified by any actions.

  • Various speed improvements to landmark factories. This is part of a larger ongoing clean-up of the landmark code.

  • More informative output, and more control over the output. The driver now prints the total runtime of all components. For many planner components, including all heuristics, the verbosity level can now be configured individually.

Details:

  • translator: Fix a bug where the translator would not check goal conditions on predicates that are not modified by actions. https://issues.fast-downward.org/issue1055

  • driver: Print overall planner resource limits and overall planner runtime on Linux and macOS systems. https://issues.fast-downward.org/issue1056

  • logging: verbosity option for all evaluators https://issues.fast-downward.org/issue921 All evaluators and heuristics now have their own configurable logger and no longer use g_log. These loggers have a verbosity option, which allows choosing between silent, normal, verbose and debug for all instances of evaluators created on the command line.

  • landmarks: Speed up landmark generation time by 10-20% for lm_rhw, lm_zg, and lm_exhaust by avoiding unnecessary computations in the landmark exploration. https://issues.fast-downward.org/issue1044

  • landmarks: Speed up landmark generation time by 5-15% for lm_rhw, lm_zg, and lm_exhaust by computing reachability in the landmark exploration as boolean information instead of (unused) integer cost/level information. https://issues.fast-downward.org/issue1045

  • landmarks: Improve landmark dead-end detection so that relevant static information is only computed once, instead of at every state evaluation. https://issues.fast-downward.org/issue1049

  • infrastructure: Upgrade GitHub Actions to Windows Server 2019 (Visual Studio Enterprise 2019) and Windows Server 2022 (Visual Studio Enterprise 2022). Remove Windows Server 2016, because GitHub Actions no longer support it. https://issues.fast-downward.org/issue1054

  • infrastructure: Run GitHub Actions only for the following branches: main, issue*, release-*. https://issues.fast-downward.org/issue1027

Fast Downward 21.12

Released on February 16, 2022.

Highlights:

  • Fast Downward now has a logo!

  • We added new methods for generating patterns and pattern collections based on counterexample-guided abstraction refinement and a new highly random method for generating individual patterns based on the causal graph. These methods are due to Rovner et al. (ICAPS 2019).

  • The operator-counting heuristic now has an option to use integer operator counts rather than real-valued operator counts. This makes the heuristic more accurate at a vastly increased computational cost (not generally recommended, but very useful for targeted experiments). We added a new constraint generator for Imai and Fukunaga's delete relaxation constraints (JAIR 2015). With the right option settings, the operator-counting heuristic with this new constraint generator results in the optimal delete relaxation heuristic h+.

  • Pruning methods now have a different interface. The mechanism to disable pruning automatically after a number of expansions that resulted in little pruning is now implemented as its own pruning method that wraps another pruning method. Be careful that the old syntax is still accepted by the planner, but the options that limit pruning are ignored. (This is due to an option parser bug; a fix is in the works.)

  • In our ongoing efforts to improve the landmark code, the landmark factories and landmark-count heuristic received a major overhaul. We removed irrelevant options for landmark factories, decoupled the computation of reasonable orders from landmark generation, made many internal code and data structure changes to make the code nicer to work with and fixed several long-standing bugs.

  • All pattern generators and pattern collection generators now have controllable verbosity. Similar changes to other components of the planner are planned. This is part of a general effort to make logging more configurable.

  • For developers: The internal representation of states has been overhauled, resolving the confusion between the previous classes GlobalState and State.

Details:

Fast Downward 20.06

Released on July 26, 2020.

Highlights:

  • The Singularity and Docker distributions of the planner now include LP support using the SoPlex solver out of the box. Thank you to ZIB for their solver and for giving permission to include it in the release.

  • The Vagrant distribution of the planner now includes LP support using the SoPlex and/or CPLEX solvers out of the box if they are made available when the virtual machine is first provisioned. See https://www.fast-downward.org/QuickStart for more information.

  • A long-standing bug in the computation of derived predicates has been fixed. Thanks to everyone who provided bug reports for their help and for their patience!

  • A new and much faster method for computing stubborn sets has been added to the planner.

  • The deprecated merge strategy aliases merge_linear and merge_dfp have been removed.

Details:

Fast Downward 19.12

Released on December 20, 2019.

Highlights:

  • Fast Downward no longer supports Python 2.7, which reaches its end of support on January 1, 2020. The minimum supported Python version is now 3.6.

  • Fast Downward now supports the SoPlex LP solver.

Details:

Fast Downward 19.06

Released on June 11, 2019. First time-based release.