Some Additional Notes about GOAP

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Presentation transcript:

Some Additional Notes about GOAP H. Muñoz-Avila

FSM vs Planning FSM: Planning Operators A resulting plan: Patrol Preconditions: No Monster Effects: patrolled Fight Monster in sight Patrol Fight Monster In Sight No Monster FSM: A resulting plan: Patrol patrolled Fight No Monster Monster in sight Neither is more powerful than the other one

But Planning Gives More Flexibility “Separates implementation from data” --- Orkin inference knowledge Many potential plans: Patrol Fight … Planning Operators Patrol Preconditions: No Monster Effects: patrolled Fight Monster in sight … If conditions in the state change making the current plan unfeasible: replan!

Issues: Efficiency (I) Evaluating preconditions: Current state represented in a table for rapid access Monster in sight Treasure in sight …. …. √ × (fast AI planners like TALPlan also answers with constant complexity the question if a given atom is satisfied in the current state)

Issues: Efficiency (II) Search: They use A* to guide the search Operators are prioritize according to domain knowledge …. (fast AI planners like FastForward also use heuristics to guide search)

But What About the Sussman Anomaly? Principle: Given some goals, achieving one of them will make it impossible to achieve the other ones A B C Initial State: Goal: Classical example in Blocks world: Any domain-specific strategy in Blocks world that will avoid the problem?

But… Does it Work in Practice? FEAR not!