Lesson 25 - Module 9 Planning Version 1 CSE IIT, Kharagpur...

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Module 9 Planning Version 1 CSE IIT, Kharagpur
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Lesson 25 Planning algorithm - II Version 1 CSE IIT, Kharagpur
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9.4.5 Partial-Order Planning Total-Order vs. Partial-Order Planners Any planner that maintains a partial solution as a totally ordered list of steps found so far is called a total-order planner , or a linear planner . Alternatively, if we only represent partial-order constraints on steps, then we have a partial-order planner , which is also called a non-linear planner . In this case, we specify a set of temporal constraints between pairs of steps of the form S1 < S2 meaning that step S1 comes before, but not necessarily immediately before, step S2. We also show this temporal constraint in graph form as S1 +++++++++> S2 STRIPS is a total-order planner, as are situation-space progression and regression planners Partial-order planners exhibit the property of least commitment because constraints ordering steps will only be inserted when necessary. On the other hand, situation-space progression planners make commitments about the order of steps as they try to find a solution and therefore may make mistakes from poor guesses about the right order of steps. Representing a Partial-Order Plan A partial-order plan will be represented as a graph that describes the temporal constraints between plan steps selected so far. That is, each node will represent a single step in the plan (i.e., an instance of one of the operators), and an arc will designate a temporal constraint between the two steps connected by the arc. For example, S1 ++++++++> S2 ++++++++++> S5 |\ ^ | \++++++++++++++++| | | v | ++++++> S3 ++++++> S4 ++++++ graphically represents the temporal constraints S1 < S2, S1 < S3, S1 < S4, S2 < S5, S3 < S4, and S4 < S5. This partial-order plan implicitly represents the following three total- order plans, each of which is consistent with all of the given constraints: [S1,S2,S3,S4,S5], [S1,S3,S2,S4,S5], and [S1,S3,S4,S2,S5]. 9.5 Plan-Space Planning Algorithms An alternative is to search through the space of plans rather than a space of situations . That is, we start with a simple, incomplete plan, which we call a partial plan . Then we consider ways of expanding the partial plan until we come up with a complete plan that Version 1 CSE IIT, Kharagpur
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solves the problem. We use this approach when the ordering of sub-goals affects the solution. Here one starts with a simple, incomplete plan, a partial plan, and we look at ways of expanding the partial plan until we come up with a complete plan that solves the problem. The operators for this search are operators on plans: adding a step, imposing an ordering that puts one step before another, instantiating a previously unbound variable, and so on. Therefore the solution is the final plan.
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This note was uploaded on 09/20/2010 for the course MCA DEPART 501 taught by Professor Hemant during the Fall '10 term at Institute of Computer Technology College.

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Lesson 25 - Module 9 Planning Version 1 CSE IIT, Kharagpur...

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