Examples

We present here a list of notebooks recommended to start with unified-planning.

Basic Example

In this notebook we show the basic usage of the unified planning library.

In particular we will go through the following steps:

create a classical planning problem;
call a planner to solve the problem;
go beyond plan generation showing how to validate a plan and how to ground a planning problem;
call multiple planners in parallel.

Numeric Planning

In this notebook we show how to model a numeric problem.

We will define a simple problem with counters that must be incremented.

Optimal Planning

In this notebook we show how to define a problem with an Optimality metric and how to get a solver that gives the optimal solution regarding the given metric.

Temporal Planning

In this notebook we show how to use the unified planning library to model temporal problems.

In particular we model the well-known MatchCellar problem and we call a planner to solve it.

Simple Multi-Agent Planning Problem

In this notebook shows how to use the unified planning library to model simple multi-agent problems and what heuristics the planner supports.

Depot Multi-Agent Planning Problem

In this notebook we show how to use the unified planning library to model multi-agent problems. In particular we model the well-known Depot problem and we call a planner to solve it.

Simulated Effects

In this notebook we show the simulated effects usage in the unified planning library.

In particular, we exploit the use of a simulated effects to model the battery consumption of a robot during a movement defining a function in Python code.

Compilers

In this notebook we show the usage of the operation mode “Compiler”, explaining how to use a compiler and how to take a plan written for the compiled problem and create the equivalent plan for the original problem.

Oversubscription Planning and MetaEngine Usage

In this notebook we define an oversubscription planning problem and we solve it using a MetaEngine.

Hierarchical Planning

In this notebook, we show how to use unified planning library to define hierarchical planning problem.

Sequential Simulator

In this notebook, we show how to use the SequentialSimulator.

The simulator is used to:

check action applicability in a state
see the state created by an action application
inspect fluents values during a plan execution
evaluate quality metrics during plan execution

Planning Engine Integration

In this notebook we create a new planning engine for the “OneshotPlanner” operation mode, we register the new planner in the UP library and we test it on a simple problem.

PDDL I/O

In this notebook we show how to parse a problem from PDDL in the unified_planning and how to write a unified_planning problem in PDDL.

Plan Parsing and Conversion

In this notebook we show how to parse a plan from a file (or a string) and how to convert a plan from a format to another.

MA-PDDL Writer

In this notebook we show how to write a unified_planning problem in MA-PDDL.

Task and Motion Planning

In this notebook we show how to create a Task and Motion Planning (TAMP) problem that includes a map, configurations, and movable objects that are used to impose motion constraints in TAMP operators. (Note: this example does not work in Colab because the engine uses Docker itself.)