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Graphplan is an algorithm for automated planning developed by Avrim Blum and Merrick Furst in 1995. Graphplan takes as input a planning problem expressed in STRIPS and produces, if one is possible, a sequence of operations for reaching a goal state.

In this graph, we are able to encode depth-two plans (because there are two layers of actions). Action level 1 has the actions that we might choose to do on the first step, and action level 3 has the actions we might choose to do on the second step.

May 29, 2024 · Planning graphs play a vital role in AI planning by visually representing possible states and actions that aid in decision-making. This article explores STRIP-like domains that construct and analyze the compact structure called graph planning.

Graphplan is a general-purpose planner for STRIPS-style domains, based on ideas used in graph algorithms. Given a problem statement, Graphplan explicitly constructs and annotates a compact structure called a Planning Graph, in which a plan is a kind of …

A plan graph represents facts achievable in a future level based on application of feasible operators at the present level. The first level represents the initial state, and the last level contains all the facts that appear in the goal state (as well as, possibly, many others).

Properties of planning graphs A literal that does not appear in the final level of the graph cannot be achieved by any plan. The level cost of a goal literal is the first level it appears, e.g., 0 for cleanhands and 1 for dinner.

Graph Plan propositional planner, that is, there are no variables Simpler – don’t have to worry about matching Bigger – if you have six blocks, you need 36 propositions to represent all On(x,y) assertions Make a plan graph of depth k Search for a solution If succeed, return a plan

Planning graph for heuristic search Using the planning graph to estimate the number of actions to reach a goal If a literal does not appear in the final level of the planning graph, then there is no plan that achieve this literal! h = ∞