22-06-2012, 02:04 PM
SEMINAR ON STRIPS
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In artificial intelligence, STRIPS (Stanford Research Institute Problem Solver) is an automated planner developed by Richard Fikes and Nils Nilsson in 1971. This language is the base for most of the languages for expressing automated planning problem instances in use today; such languages are commonly known as action languages.
Mathematically, a STRIPS instance is a quadruple , in which each component has the following meaning:
1. P is a set of conditions (i.e., propositional variables);
2. O is a set of operators (i.e., actions); each operator is itself a quadruple , each element being a set of conditions. These four sets specify, in order, which conditions must be true for the action to be executable, which ones must be false, which ones are made true by the action and which ones are made false;
3. I is the initial state, given as the set of conditions that are initially true (all others are assumed false);
4. G is the specification of the goal state; this is given as a pair , which specify which conditions are true and false, respectively, in order for a state to be considered a goal state.
STRIPS belongs to the class of problem solvers that search a space of "world models " to find one in which a given goal is achieved. For any world model, we assume there exists a set of applicable operators each of which transforms the world model to some other world model. The task of the problem solver is to find some composition of operators that transforms a given initial world model into one that 'satisfies some particular goal condition. This framework for problem solving, discussed at length by Nilsson, has been central to much of the research in Artificial Intelligence. A wide variety of different kinds of problems can be posed in this framework. Goals and subgoals for STRIPS will be stated as first-order predicate calculus wffs (well formed formulas). For example, the task push a box to place b " might be stated as the wff (3:u) (BOX(u) !\ AT(u, b)), where the predicates have the obvious interpretation The task of the system is to find a sequence of operators that will produce a world model in which the goal can be shown to be true.