Managing Problems using rddlrepository#

The rddlrepository:

hosts a diverse collection of domain and instance RDDL files, covering problems from a wide range of disciplines (full listing here)
includes all domains used in the probabilistic and learning track of the International Planning Competitions (2011, 2014, 2018, 2023)
is updated and expanded frequently with the help of the community
contains custom visualizers for a subset of domains, to be used with the pyRDDLGym package
provides out-of-the-box compatibility with pyRDDLGym.

Installing#

To install with pip:

pip install rddlrepository

Note

If you are reinstalling a new version of rddlrepository on top of an old one, you must rebuild the manifest. If you are using an older version of rddlrepository < 2.2, you must go to your installation directory of rddlrepository and delete the manifest.csv file in the core subdirectory (it will be rebuilt automatically). If you are using a new version of rddlrepository >= 2.2, simply open a console in your current Python environment and type rddlrepo build.

Retrieving Information about Domains and Instances#

The core object for extracting domains and instances is the RDDLRepoManager object:

from rddlrepository.core.manager import RDDLRepoManager
manager = RDDLRepoManager(rebuild=True)

Note

rebuild instructs the manager to rebuild the manifest, which is an index containing the locations of all domains and instances for fast access. While you do not need this option in normal operation, in case you add your own domains or the manifest becomes corrupt, you can force it to be recreated.

Listing Available Domains#

To list all domains currently available in rddlrepository:

print(manager.list_problems())

Domains are organized by context (e.g. competition year, benchmark set) with names usually following the syntax <domain name>_<context> (except for standalone domains where the context is excluded from the name)

print(manager.list_context())
print(manager.list_problems_by_context("standalone"))   # list all standalone problems
print(manager.list_problems_by_context("ippc2018"))     # list all problems from IPPC 2018

Retrieving Information about a Domain or Instance#

The information for a specific domain is stored in a ProblemInfo instance:

problem_info = manager.get_problem("EarthObservation_ippc2018")

will load the EarthObservation domain from the ippc2018 context.

To list all the instances of a domain:

print(problem_info.list_instances())

To return the paths of the domain and instance:

print(problem_info.get_domain())
print(problem_info.get_instance("1"))

To return the pyRDDLGym visualizer class:

viz_class = problem_info.get_visualizer()

Loading an Environment in pyRDDLGym#

In the introduction to pyRDDLGym, we presented the recommended way to load an environment:

import pyRDDLGym
env = pyRDDLGym.make("EarthObservation_ippc2018", "1")

This can also be done explicitly using rddlrepository:

problem_info = manager.get_problem("EarthObservation_ippc2018")
env = pyRDDLGym.make(domain=problem_info.get_domain(), instance=problem_info.get_instance("1"))
env.set_visualizer(problem_info.get_visualizer())

Registering a New Domain or Instance#

To register a new context in rddlrepository for later access:

manager.register_context("MyContext")

To register a new domain in a given context for later access:

domain_content = """
    domain ... {
        ...
    }
"""
manager.register_domain("MyDomain", "MyContext", domain_content,
                        desc="a description of this domain", viz="ModuleName.ClassName")

Here, "ModuleName.ClassName" refers to the Module name and the Class name of the visualizer (optional).

To register an instance for an existing domain for later access:

instance_content = """
    instance ... {
        ...
    }
"""
problem_info.register_instance("MyInstance", instance_content)