Mathias Bauer -
Susanne Biundo -
Harald Feibel - Jana Koehler - Gabriele Paul
PHI is a logic-based system which improves the performance of
intelligent help systems by supplying them with plan generation and plan
recognition components. Both components work in close mutual cooperation.
There are two modes of cross-talk between them, one where plan recognition
is done on the basis of abstract plans provided by the planner and the
other where optimal plans are generated based on recognition results. The
system works in an operating system domain, namely the UNIX mail
Intelligent help systems aim at providing advanced active help to the
users of complex software systems. The performance of these help
systems can be considerably improved if they are supplied with
plan recognition and plan generation capabilities.
Observing a user and recognizing his goals enables the system to help
by taking into account the current state of the system as well as the
user's level of education and current behavior. Moreover, if a
planning capability is available user-specific support can be given by
proposing appropriate plans which exactly is what the PHI system aims
One of the main characteristics of PHI consists in the close mutual
cooperation between the planner and the plan recognizer.
There are two cross-talk modes :
In the first cross-talk mode the plan recognizer is able to determine
the most likely plan a user follows by carrying out appropriate
``instantiations'' on valid plan hypotheses. Thus, services like
semantic plan completion can be offered at any time during the
The second cross-talk mode is devoted to providing the user with
optimal plans whenever suboptimal behavior has been recognized
or aid has explicitly been sought.
Planning and Plan Reuse
The generation of plans is based on standard assumptions concerning
goals that typically occur or are specific to a certain user. Abstract
plans are generated from these formal plan specifications. In doing
so, the planner not only performs planning from first principles but
is able to reuse already existing plans which are stored in
a library (planning from second principles).
Plans serve as hypotheses in the recognition process.
Taking abstract plans instead of concrete ones keeps the hypothesis
space of manageable size. The plan hypotheses are passed to the
recognition component where they are provided with numerical values
which reflect the probabilities of their being confirmed by the
subsequent observations. These a priori probabilities mirror a
specific user's behavior, and are taken from the user model. Having
observed the user's actions step by step the plan recognizer
consequently tries to confirm the plan hypotheses by proving that the
action sequence observed up to now is an admissible ``instance''.
Hypotheses which are not confirmed are rejected and with that the
probability distribution of the hypothesis space changes dynamically.
Abstract plans are those which represent a variety of
``concrete'' observable action sequences by admitting several degrees
of freedom like variables (abstracting from the objects involved),
abstract commands (abstracting from the names of actions which have
the same effects), or temporal abstraction (abstracting from the point
in time at which an action occurs).
The Planning Logic
The system is completely logic-based. It requires a proper
axiomatization of the basic commands of the application system and certain
domain constraints. The logic LLP which we have developed for
that purpose combines features of both traditional programming and temporal
logics. The plan generation and recognition components are special purpose
inference procedures. Plan generation is done deductively using a
sequent calculus for LLP, whereas plan recognition follows an
The application domain is a subset of the operating system UNIX,
namely its mail system , where commands like type, delete,
or manipulate objects like messages or mailboxes.
Realizing plan generation and recognition in a strictly logic-based
way nevertheless does not cause any considerable inefficiencies, even for
``real'' plans. This suggests evaluating the PHI
approach even for richer application domains. A prototype of the PHI
system has been implemented in SICSTUS PROLOG on a SUN SPARC
The system IGLOO is an interactive, graphic supported proof development
environment for sequent calculi. It was implemented as a master thesis' work
within the PHI project. It provides a valuable support for the development of
proof guiding tactics. These tactics are necessary for an efficient deductive
planner generating plans by proving plan specifications (LLP
formulas specifying the goals to be reached by a plan) constructively.
Acknowledgement: The PHI Projekt was supported by the
German Ministry for Research and Technology (BMFT) under contract