Cypress is an integrated planning framework that supports a wide range of
planning and execution activities, including activities that require
extensive interactions among its subsystems. Here, we describe how a user
might exercise the full extent of Cypress for a typical application.
The first step for any application is to represent the possible actions
for the domain. These actions are defined (using the Act-Editor) as a
collection of Acts which can be translated into the internal
operator/procedure representations of both the planner and executor.
A typical use of Cypress to implement a taskable, reactive agent has the
executor continually monitoring the world for additional goals and events
that might require action in response. When a plan is required or
requested (in response to an event in the world), the executor makes the
appropriate request of the planner. The executor continues to monitor and
respond to the world while the planner plans. The plans generated by the
planner are translated to Acts for execution. The executor executes the
plans produced by using Acts at lower levels of abstraction to perform
actions that have not been explicitly planned, and invokes the planner when
replanning is required.
Using the operators translated from the Act representation, the planner
generates plans in response to user-specified goals. The user can
optionally instruct the planner to automatically employ the uncertain
reasoner to reason about uncertain information while making decisions in
the planning process. In particular, the uncertain reasoner can be invoked
to choose among alternative objects and resources for use in the plan and
to choose among alternative operators that can be applied to achieve a
goal, based on user-supplied domain information. The uncertain reasoner
can be called by the executor during plan execution when so directed by an
Act. Thus, the domain programmer indicates those situations in which the
uncertain reasoner should be employed.
Cypress supports run-time replanning. Should an unexpected problem arise
during execution of the plan, the executor recognizes the problem, calls
the planner to produce a new plan, and continues executing those portions
of the plan that were not affected by the problem. Upon receiving a new
plan, the executor would reconcile it with its current state and continue
execution.
Joint Military Operations
Cypress has been applied to joint military operations planning, in a
manner that parallels the above description. For this application, the
planner uses domain knowledge in the form of Acts to generate employment
and deployment plans for dealing with specific enemy threats, using the
uncertain reasoner to choose military units based on uncertain information
about both friendly and enemy units. (Click here
for more details on planning in this domain.)
The plan is translated to an Act for
execution, and the executor employs a suite of lower-level Acts during
execution that define the execution steps for the actions that the planner
assumes as primitive. The executor responds to unexpected events with Acts
that encode standard operating procedures. When execution of the plan
reaches an impasse because of some unexpected changes in the world, it
invokes the planner to provide an alternative plan, while continuing
execution of activities not affected by the failure.
A critical issue in any application is dividing responsibility between the
planner and executor. In principle, each can execute Acts at any level of
abstraction. In practice, the planner should not plan to the lowest level
of detail and the execution system should not execute very abstract
actions, unless forced to do so by time limitations. For these reasons, a
fixed level of abstraction is specified for each application that serves as
an interface level between planning and execution. The planner plans
down only to the interface level, while the executor will accept plans at
that level and attempt to execute them using actions from that level of
abstraction or below. For the military operations domain, nine levels of
abstraction are employed in representing domain actions. The planner plans
through five levels of abstraction, at which point actions are at the level
of deploying forces, mobilizing units, and establishing patrols. The
executor employs Acts from the remaining four levels of abstraction during
execution. There are no recursive operators in these levels; thus, the
executor performs at most four levels of subgoaling for this domain.
John D. Lowrance,
<lowrance@ai.sri.com>
Karen L. Myers,
<myers@ai.sri.com>
David E. Wilkins,
<wilkins@ai.sri.com>
Artificial Intelligence Center
SRI International
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