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3.3 Planning

MOVERS-WORLD presents a challenging planning domain. Each problem requires the actors to move from 3 to 5 boxes of various sizes to the truck. The baseline system initially takes, on average, 38.6 rounds of activity to solve a problem. At any given point in time, an actor's knowledge of the external world is her perceivable environment and a map of the world that she constructs as she goes along. Plans orient the individual actor as to how to proceed (c.f., [70]) but, because of uncertainty in acting, plans are continuously being revised. Actors are assumed to be adaptive planners [4], so if the activity does not unfold as anticipated, the actor's plan will be revised to reflect the ongoing interaction between the actor and her environment. In general, activity may not go as expected for a variety of reasons:

1.
An actor may be interrupted by a request from another actor. In this case, the actors have a conversation. During the conversation, actors may choose to suspend their current goals and plan to accommodate a request [5.2 times per problem]. Alternatively, an actor may have to abandon her current goals and plan because the other actor can not or will not provide the needed assistance [6.4 times per problem].
2.
An actor may attempt a primitive action which fails because of the actor's lack of omniscience about the domain [12.2 times per problem].
3.
In some cases there may be a resource conflict among actors, i.e. more than one actor tries to manipulate the same object. Currently, the outcomes of these are decided at random and the `losing' actors are delayed [4.1 times per problem].
4.
Joint-actions are an all-or-nothing proposition. Unless all relevant actors participate, those that attempt to participate fail [< 0.1 times per problem].
5.
An actor's attempt to communicate with another actor may be unsuccessful since the other actor's communication channel may be busy or the other actor may be refusing to answer (see Section 3.4) [12.7 times per problem].

For these reasons, actors will frequently have to adapt, replan, or suspend the current activity. When a plan is completed or abandoned, the actor must select a new set of goals to plan for. At each point in the activity, goals are marked as either `untried', `active', `suspended', `failed', or `completed' and are prioritized during the goal selection process:

1.
untried goals
2.
suspended goals
3.
failed goals

A plan is created for a set of goals by either selecting an old plan from memory or creating a plan from scratch. Old plans are stored somewhat abstractly so they require some refinement before they are deployed; our model differs from others in that extracts of execution traces are stored in memory and not plans [18,56,43] or derivational histories [10,73] Others have studied re-using past plans under other conditions [35], including multiple actors [71].

An actor can create a plan from scratch using a given set of STRIPS-like operators [19] in a hierarchical planner (c.f. [63,44]). Depending on their type, different actors have different operations that they can perform. The special purpose operators for the actors in MOVERS-WORLD are:

lifter
LIFT, LIFT-TOGETHER, CARRY, CARRY-TOGETHER, LOAD, LOAD-TOGETHER, UNLOAD, UNLOAD-TOGETHER, PUT-DOWN, and PUT-DOWN-TOGETHER.
hand-truck operator
PUSH-HANDTR, TILT-HANDTR, and STAND-HANDTR.

There are also general purpose operators that any actor can perform, i.e.,

MOVE, WAIT, or SIGN.
Each actor maintains a representation of the probability of success for different actions in different contexts. When planning from scratch, the actor uses these probabilities to guide it through the search space [46]. This information represents some of the expectations the individual actor has about the capabilities of herself and her co-participants. The probabilities are incrementally updated, so the actor develops more realistic expectations during the course of action.



Subsections
Next: 3.3.1 Operator Probability Trees Up: 3. MOVERS-WORLD Previous: 3.2 The Community
Last Update: March 10, 1999 by Andy Garland