By James Allen, Henry Kautz, Richard Pelavin, Josh Tenenberg
This ebook provides 4 contributions to making plans study inside of an built-in framework. James Allen bargains a survey of his study within the box of temporal reasoning, after which describes a making plans process formalized and applied at once as an inference approach within the temporal common sense. ranging from an identical good judgment, Henry Kautz develops the 1st formal specification of the plan attractiveness strategy and develops a strong kin of algorithms for plan reputation in complicated events. Richard Pelavin then extends the temporal good judgment with version operators that permit the illustration to aid reasoning approximately advanced making plans events regarding simultaneous interacting activities, and interplay with exterior occasions. eventually, Josh Tenenberg introduces diversified formalisms of abstraction in making plans structures and explores the houses of those abstraction strategies in depth.
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Extra info for Reasoning About Plans
This will require further chaining to prove [Stack A Β E l T l ] . This process of creating event and temporal constants to replace the unbound variables will be called instantiating the planning rule. And finally, we need to elaborate on assumption making. There are two special ways in which a literal may be "proven" entirely by assumption. The first is an ability assumption in which an agent may assume that it can try any action that it chooses. Thus, any literal of the form Try(a,e,t) is trivially proven by assumption.
The goal stack now contains one goal: G S : [On Β C Obc]. t' bound to Obc. e to a new event constant E3, and adds the assumption [EQ Obc eff2(E3)] and the temporal constraints for the new stacking event E 3 . The new goal stack is simply G S : [Stack Β C E3 T4]. t to T4. The left-hand side of (Stack 3) is added to the goal stack, which now is G S : [Clear Β prel(E3)] [Clear C pre2(E3)] [Try [stack Β C] E3 T4]. [Clear Β prel(E3)] can be proven by a persistence assumption from [Clear Β Cb], [Clear C pre2(E3)] from a persistence assumption from [Clear C Cc], and [Try [stack Β C] E3 T4] is proven since it is under the agent's control.
On the other hand, the hierarchical planners such as NOAH [Sacerdoti 1977], NONLIN [Tate 1977], SIPE [Wilkins 1988], and FORBIN [Dean, Firby, and Miller 1989], use preexisting knowledge about how to achieve single goals and reason about how to combine these simple tasks into more complex ones that achieve multiple goals simultaneously. Typically, this involves detecting interactions between the 34 TEMPORAL REASONING AND PLANNING simple tasks and imposing ordering constraints on the substeps of each task so that they do not interfere with each other.
Reasoning About Plans by James Allen, Henry Kautz, Richard Pelavin, Josh Tenenberg