Welcome to LAPKT!
What is LAPKT?
LAPKT stands for the Lightweight Automated Planning ToolKiT. It aims to make your life easier if your purpose is to create, use or extend basic to advanced Automated Planners. It's an open-source Toolkit written in C++ and Python with simple interfaces that give you complete flexibility by decoupling parsers from problem representations and algorithms. It has been succesfully used in embedded systems, webservices, and contains some of the high-performance planners from the last International Planning Competition 2014.
LAPKT separates search engines from the data structures used to represent planning tasks. This second component receives the name of ‘interface’ since it is indeed the interface that provides the search model to be solved.
At the moment of writing this, the following interfaces are offered:
- ‘agnostic’: this interface does not depend on a particular planning language, so it is easy to wrap PDDL parsers, separating parsing representation of planning tasks from a representation optimized for off-line planning. This interface should also make easy to integrate STRIPS planners into applications by suitably defining planning tasks programatically.
- ‘ff’: this interface wraps FF parsing components to obtain ‘agnostic’ looking tasks.
Future interfaces planned are:
- ‘hsps’: this interface wraps Patrik Haslum’s HSP codebase, which supports parsing of PDDL 3.0 features.
- ‘SAS+’: this interface is meant to support SAS representations natively. Since there is no SAS-based planning language, this will probably be useful to integrate planners into applications that are able to define SAS planning tasks programatically.
Search engine components are meant to be modular, allowing users of LAPKT to assemble and combine features of different search engines to come up with customized search strategies, within reason and without sacrificing (much) efficiency. In order to do so, LAPKT makes heavy use of C++ templates and the Static Strategy design pattern. At the time of writing this, the modularity and decoupling of components isn’t as high as I would like, there’s still a lot of work to do :)
LAPKT is bound to change rapidly and dramatically over the next months, so please keep this in mind when using this library.
In order to build LAPKT you need to install scons (a GNU Makefile replacement) in your system. Refer to http://www.scons.org for directions on how to achieve this.
In order to compile some of the examples, you will also need a version >= 1.49 of the Boost C++ libraries available on your system. You can check the version you have either manually by looking at the macro defined in
boost/version.hpp or, on debian systems, by running
dpkg -s libboost-dev. Be aware that systems such as the Ubuntu 12.04LTS release ship with older versions of Boost.
Finally, LAPKT requires the Judy library (http://judy.sourceforge.net/index.html) to support the bitmap array class ‘Varset Judy’. NOTE: This dependency will be optional or entirely deprecated in the future.
Search Algorithms Implemented
Any-time Best First Search.
Any-time Best First Search with two open lists (the PREFERRED list, for nodes generated by preferred operators, and the OPEN list, for the rest).
Best First Search with three open lists and two heuristic estimators. The search frontier is split into three lists:
BOTH: holds nodes generated by actions deemed as 'preferred' by both heuristic estimators PREFERRED: holds nodes generated by actions deemed as 'preferred' by the primary heuristic estimator OPEN: holds nodes generated by actions not deemed as 'preferred' by the primary heuristic estimator
- include/aptk/at_wbfs.hxx, include/aptk/at_wbfs_dq.hxx, include/aptk/at_wbfs_dq_mh.hxx
Any-time Weighted A*, with weight W decaying according to fixed decay parameter. Variants include single queue and multiple queue (either with one or two heuristic estimators).
- include/aptk/at_rwbfs.hxx, include/aptk/at_rwbfs_dq.hxx, include/aptk/at_rwbfs_dq_mh.hxx
Any-time Restarting Weighted A* described on
with weight W decaying according to fixed decay parameter. Variants include single queue and multiple queue (either with one or two heuristic estimators).
The Deadline Aware Search algorithm described in
Agnostic Interface Examples
The examples for the ‘planner agnostic’ interface can be found on
and cover the following topics:
* agnostic-examples/assembling_strips_problems Shows how to define a STRIPS planning problem programatically. * agnostic-examples/successor_generation Discusses the different way of generating successors during search. * agnostic-examples/bfs * agnostic-examples/bfs-double-queue * agnostic-examples/bfs-double-queue-secondary-heuristic Shows how can one assemble available components to deliver a planner built around a BFS search engine, with multiple queues and secondary heuristics, on a parametrized planning task. * agnostic-examples/das Shows how can one assemble available components to deliver a planner built around Deadline Aware Search.
Anybody can contribute to LAPKT by submitting code or patches to