Artificial Intelligence


The common standard for solve a symbolic problem is to create first the PDDL file which contains the domain description. The precondition, effects and action names are given in the PDDL file and a graph based planner can search in the state space for a plan. A typical example algorithm is Probabilistic roadmap (PRM) which is generating a graph of the statespace.[1]

What makes absolutely no sense, is to modify the planning problem by relaxing the boolean constraints of the action primitives. In a normal PDDL file, the effect is always true or false. Which means, after a robot opens the door, the variable is true because the action was successful. Using multivalue logic for describing the effects in the PDDL file is an antipattern and will make the overall planning procedure more complicated.[2]


  1. Garrett, Caelan Reed, Tomas Lozano-Perez, and Leslie Pack Kaelbling. "FFRob: Leveraging symbolic planning for efficient task and motion planning." The International Journal of Robotics Research 37.1 (2018): 104-136.
  2. Jobczyk, Krystian. Temporal planning with fuzzy constraints and preferences. Diss. Normandie Université, 2017.