# 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 () and the issue tracker (). Repository branches are named after the corresponding tracker issues. ## Changes since the last release No changes yet. ## 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: - new Fast Downward logo You can see the logo in the README file on . Check out for alternative suggestions including the ever so popular "truck falling down the hill" logo. - fast-downward.py main script: The script now automatically finds domain files `-domain.` for task files called `.` - pdbs: Integrate the Rovner et al. pattern generation methods based on CEGAR. - pdbs: Integrate the Rovner et al. random pattern generation methods. - pdbs: All pattern (collection) generators now have an option `verbosity` to set the desired level of output. Internally, generators now use their own logger rather than g_log. - pdbs, for developers: Replace size_t by int for abstract state hashes in PDB-related code. - LP/IP: Support integer variables in linear programs. You can now use the LP solver interface to solve mixed integer programs. In particular, the operator-counting heuristics now have an option `use_integer_operator_counts` that improves the heuristic value by forcing operator counts to take integer values. Solving a MIP is NP-hard and usually takes much longer than solving the corresponding LP. - LP/IP: Delete-relation constraints can now be used in the operator-counting framework. The constraints defined by Imai and Fukunaga (JAIR 2015) encode different relaxations of the delete-relaxation heuristic. For details, see - LP/IP: Fix a bug which induced inadmissible heuristic values when solving MIPs. This only occurred for operator-counting heuristics with integer variables and very large heuristic values (at least 10,000). - LP/IP, for developers: Add debugging methods to LP solver interface. You can now assign names to LP variables and constraints for easier debugging. Since this incurs a slight runtime penalty, we recommend against using this feature when running experiments. - LP/IP, for developers: Debug builds with LP solvers vs. the `_GLIBCXX_DEBUG` flag. Previously, we used the flag `_GLIBCXX_DEBUG` in debug builds for additional checks. This makes the binary incompatible with external libraries such as LP solvers. The flag is now disabled by default. If no LP solvers are present or LP solvers are disabled, it can be enabled by setting the CMake option `USE_GLIBCXX_DEBUG`. The build configurations `debugnolp` and `releasenolp` have been removed, and the build configuration `glibcxx_debug` has been added. - pruning: New `LimitedPruning` class replaces previous limitation options of individual pruning methods. For example, the old command line `--search "astar(lmcut(),pruning=atom_centric_stubborn_sets(min_required_pruning_ratio=0.2,expansions_before_checking_pruning_ratio=1000))"` is now expressed as `--search "astar(lmcut(),pruning=limited_pruning(pruning=atom_centric_stubborn_sets(),min_required_pruning_ratio=0.2,expansions_before_checking_pruning_ratio=1000))` - landmarks: Replace landmark factory option `reasonable_orders` by the new landmark factory `lm_reasonable_orders_hps`. For example, the old command line `--evaluator hlm=lmcount(lm_factory=lm_rhw(reasonable_orders=true))` is now expressed as `--evaluator hlm=lmcount(lm_factory=lm_reasonable_orders_hps(lm_rhw()))` - landmarks: Replace landmark factory option `no_orders` by the new option `use_orders` with the opposite meaning. - landmarks: Removed landmark factory options that have no effect. Removed options: `lm_exhaust`: `disjunctive_landmarks`, `conjunctive_landmarks` `lm_hm`: `disjunctive_landmarks`, `only_causal_landmarks` `lm_merged`: `disjunctive_landmarks`, `conjunctive_landmarks`, `only_causal_landmarks` `lm_rhw`: `conjunctive_landmarks`, `reasonable_orders` `lm_zg`: `disjunctive_landmarks`, `conjunctive_landmarks`, `only_causal_landmarks` - landmarks: Fix a bug where `lm_rhw` would compute wrong greedy-necessary orderings in certain cases. - landmarks: Fix a bug where the `lm_rhw`, `lm_zg` and `lm_exhaust` landmark factories used an overly optimistic approximation of relaxed reachability for planning tasks with conditional effects. This change can lead to more generated landmarks and landmark orderings in such tasks. - landmarks: Fix a bug where the Zhu/Givan landmark factory caused a crash on relaxed unsolvable tasks due to an empty landmark graph. - landmarks: Fix a bug where cycles of natural orderings resulted in crashes in the landmark factories. This could only happen in unsolvable planning tasks. - landmarks: Fix a failing assertion in the `lm_rhw` landmark factory triggered by certain unsolvable tasks. - landmarks, for developers: Clean up the code of `LandmarkGraph`. Some of the public methods were renamed. This class will undergo further changes in the future. - landmarks, for developers: Separate the functionality of landmarks from the functionality of landmark nodes by introducing a new `Landmark` class. - landmarks, for developers: Move functionality used during search away from `LandmarkGraph`, making the landmark graph constant after creation. - landmarks, for developers: Introduce new class `LandmarkFactoryRelaxation` for landmark factories based on delete relaxation. Move usage of exploration object to subclasses of the landmark factory base class. - build: The build system now prefers compilers `cc`/`c++` found on the path over `gcc`/`g++`. As before, environment variables `CC`/`CXX` can be used to override this choice. - build: Only build configurations defined in `build_configs.py` are loaded in the `build.py` script. - for developers: Add option to use a local (configurable) logger instead of the global one. Classes which want to configure the logger (currently only the verbosity level can be configured) should now use the functions `add_log_options_to_parser` and `get_log_from_options` to obtain their local log object. - for developers: Unify the `State` and `GlobalState` classes. We unified the classes `GlobalState` and `State` into a new class also called `State`. This removed a lot of code duplication and hacks from the code. A description of the new class can be found in the wiki: - for developers: Change public interface of generation of random ints and doubles in the `RandomNumberGenerator` class. - for developers: Use `RandomNumberGenerator` class in `VariableOrderFinder`. - infrastructure: Add support for GitHub actions. - infrastructure: Add CPLEX support to our GitHub Actions for Windows. - infrastructure: Decide on rules regarding software support and improve GitHub actions accordingly. ## 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 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: - Fix crash of `--show-aliases` option of fast-downward.py. - Fix incorrect computation of derived predicates. Derived predicates that were only needed in negated form and cyclically depended on other derived predicates could be computed incorrectly. - Integrate new pruning method `atom_centric_stubborn_sets`. We merged the code for the SoCS 2020 paper "An Atom-Centric Perspective on Stubborn Sets" (). See . - Remove deprecated merge strategy aliases `merge_linear` and `merge_dfp`. The deprecated merge strategy aliases `merge_linear` for linear merge strategies and `merge_dfp` for the DFP merge strategy are no longer available. See https://www.fast-downward.org/Doc/MergeStrategy for equivalent command line options to use these merge strategies. - For developers: use global logging mechanism for all output. All output of the planner is now handled by a global logging mechanism, which prefaces printed lines with time and memory information. For developers, this means that output should no longer be passed to `cout` but to `utils::g_log`. Further changes to logging are in the works. - For developers: store enum options as enums (not ints) in Options objects. - For developers: allow creating Timers in stopped state. ## 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: - general: raise minimum supported Python version to 3.6 Fast Downward now requires Python 3.6 or newer; support for Python 2.7 and Python 3.2-3.5 has been dropped. The main reason for this change is Python 2 reaching its end of support on January 1, 2020. See https://python3statement.org/ for more background. - LP solver: add support for the solver [SoPlex](https://soplex.zib.de/) The relative performance of CPLEX and SoPlex depends on the domain and configuration with each solver outperforming the other in some cases. See the issue for a more detailed discussion of performance. - LP solver: add support for version 12.9 of CPLEX Older versions are still supported but we recommend using 12.9. In our experiments, we saw performance differences between version 12.8 and 12.9, as well as between using static and dynamic linking. However, on average there was no significant advantage for any configuration. See the issue for details. - LP solver: update build instructions of the open solver interface The way we recommend building OSI now links dynamically against the solvers and uses zlib. If your existing OSI installation stops working, try installing zlib (sudo apt install zlib1g-dev) or re-install OSI (https://www.fast-downward.org/LPBuildInstructions). - merge-and-shrink: remove trivial factors When the merge-and-shrink computation terminates with several factors (due to using a time limit), only keep those factors that are non-trivial, i.e., which have a non-goal state or which represent a non-total function. - tests: use pytest for running most tests - tests: test Python code with all supported Python versions using tox - tests: adjust style of Python code as suggested by flake8 and add this style check to the continuous integration test suite - scripts: move Stone Soup generator scripts to separate repository at https://github.com/aibasel/stonesoup. ## Fast Downward 19.06 Released on June 11, 2019. First time-based release.