This tool will dynamically generate a domain based on the Planning Domain Definition Language. It contains a Java program that can translate a domain specification written in the Planning Domain Definition Language (PDDL) 1.2 into a Python SML environment and a set of Soar rules that propose legal operators. The program was generated by ANTLR v3.1.3 from a PDDL grammar written by Zeyn Saigol at University of Birmingham.

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PDDL domains are usually described in two files - one that defines the domain dynamics, and one that defines the initial conditions of a specific problem within that domain. You must translate both of these files into Python SML code in order to run the environment.

To run the translator, make sure that antlr-3.1.3.jar and pddl_trans.jar are in your Java classpath, and enter the following command to the shell:

java translate <pddl file>

If the PDDL file is a domain definition, the translator will output two files:

output/<domain_name>/<domain_name>.py
output/<domain_name>/rules.soar

If the PDDL file is a problem definition, the translator will output a single file:

output/<domain_name>/<problem_name>.py

In addition to these files, there are also several Python scripts that need to be included by all domains in the python/ subdirectory, as well as some rules that need to be sourced by all agents in pddl-base.soar.

To run an agent in a generated environment, you must create an instance of the problem class (NOT the domain class), then create an instance of SmlCommandHandler using the problem object and an SML agent. This will register callback functions with the Soar agent to initialize the environment state on the input link and change it in response to commands sent to the output link. See example.py for details on how to do this.

Developer
  • Joseph Xu
Soar Versions
  • Soar 8, 9
Language
  • Java, Python