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Capabilities
Planning
PRODIGY solves problems by generating plans that consist of a sequence
of instantiated operators. The PLANNER/PROBLEM
SOLVER uses domain knowledge and applicable control knowledge to
make efficient plans. Control knowledge may include stored plans.
The ALPINE learning module fascilitates
abstract planning.
Prediction
PRODIGY is capable of prediction. Any changes to PRODIGY's simulated
environment result from PRODIGY's actions
in this environment. The effects of a single acton--the application of
an operator is part of the domain knowledge. The range of the
predictability therefore depends on the depth of the search tree that
the problem solver can generate.
Meta-Reasoning
Control rules generated by the EBL module
and the STATIC module enable
meta-reasoning. Control rules provide knowledge about the operators
given in a problem domain. This knowledge uses the same representation
as the domain knowledge.
Reactivity
PRODIGY is not designed to react to changes in a dynamic environment.
PRODIGY operates in environments defined by problem domains. Changes to
the environment result only from the application of operators.
Taskability
In a given problem domain, PRODIGY performs tasks specified by the
user. Taskability is determined by the ability of the PLANNER/PROBLEM SOLVER to find a solutions for
given problems. The architecture is intended to be highly
taskable.
Learning
PRODIGY is capable of several methods of learning. Separate learning modules employ different methods. The
system heavily employs explanation-based
learning, abstract plan generation,
and static domain analysis. All learning
in PRODIGY is deliberative.
Natural Language Processing
No natural language processing capability is provided by the architecture at
present. The APPRENTICE learning module
provides an interface with the user. It does not interpret natural language
input.
Interruptability
PRODIGY does not support this capability.
Navigation/Manipulation
PRODIGY does not have these capabilities because it does not operate
in the real world.
Coherent Behavior
PRODIGY exhibiits coherent behavior. When given a problem to solve, it
devotes itself to solving this problem.
Perception
PRODIGY does not have this capability because it operates in a
simulated environment.
Other