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ENHSP: Expressive Numeric Heuristic Search Planner

Page Contributors: Adam Green,

tags: temporal numeric

Year Published: 2016

Paper: Interval-Based Relaxation for General Numeric Planning [Scala, E. Haslum, P. Thiebaux, S. Ramirez, M.]

ENHSP, which stands for Expressive Numeric Heuristic Planner is a forward heuristic search planner. It supports PDDL2.1 and discretised PDDL+, in particular:

  1. Satisficing and Optimal Simple Numeric Planning (see below)
  2. Satisficing Numeric Planning with linear and non-linear expressions
  3. Planning with discretised autonomous processes and events
  4. Global constraints, which are the analogous of always constraints of PDDL
  5. Good support for general quantifier-free formulas
  6. Universal and existential quantification in formulas (action precondition, constraints and goals). This is hardly experimental.
  7. A variety of heuristics (e.g., hadd, aibr, haddabs, landmarks) and search mechanisms (e.g., wastar, idastar, dfsbnb)

Support

ENHSP requires :typing in all domains it runs on, which makes it incompatible with Eviscerator. No support table has been generated.

Downloading and Compiling ENHSP

For more information on how to download, compile and use ENHSP, visit its GitLab page here or ENHSP website here. The planner is mantained by Enrico Scala (enricos83@gmail.com for any question).

Additional Notes

  • ENHSP grounding is not optimised; this can become a bottleneck when your action schema induce several even trivial groundings.
  • ENHSP does not support durative actions
  • Conditional effects are supported but are highly experimental
  • Optimal planning is only supported for what is called simple numeric planning (including classical planning), i.e., only increase/decrease effects of constants, and only linear numeric conditions. Objective function can be linear combination of numeric fluents. If no objective function is given, the planner minimises the number of actions.
  • ENHSP is designed to experiment on numeric reasoning. If your problem is a purely classical planning problem, it is better to use a classical planner like FD, or even FF.

Other Relevant Papers ENHSP is built on

Heuristics for Numeric Planning via Subgoaling [Scala, E., Haslum, P. and Thiébaux, S.] Landmarks for Numeric Planning Problems [Scala, E. Haslum, P. Thiebaux, S. and Magazzeni D.] Effect-Abstraction Based Relaxation for Linear Numeric Planning [Li, D. Scala, E. Haslum, P. and Bogomolov, S]