[ont.events] U of Toronto Computer Science late announcements, May 6

clarke@utcsri.UUCP (04/29/87)

[On account of a minor accident of otherwise very little interest, the regular
notice for this week is unavailable.]

         (SF = Sandford Fleming Building, 10 King's College Road)
              (GB = Galbraith Building, 35 St. George Street)

SUMMARY:

SYSTEMS SEMINAR, Wednesday, May 6, 11 am, SF1101 -- Dr. Marc Abrams:
     ``Analysis of Distributed Programs With Periodic Equilibrium Behavior"

GRAPHICS SEMINAR, Wednesday, May 6, 2 pm, GB120 -- Professor David Zeltzer:
     ``Motor problem solving for three dimensional computer animation"

--------------------

             SYSTEMS SEMINAR, Wednesday, May 6, 11 am, SF1101

                              Dr. Marc Abrams
                      IBM Zurich Research Laboratory

                 ``Analysis of Distributed Programs With
                      Periodic Equilibrium Behavior"

     The state of many continuous physical systems (e.g., an electrical
circuit) may reach a fixed value as time grows to infinity.  Alternately,
the system may reach a limit cycle behavior, in which the stable system
state varies periodically in time. Certain distributed programs display
similar behavior. During execution, they quickly enter one of several
periodic or oscillating modes.  The mode reached depends on the process
starting order, communication delay, and the structure and timing of pro-
cess synchronization.  This talk describes a novel performance analysis
technique, the geometric concurrency model. It predicts the sequence of
synchronization points where a program blocks, the blocking durations, and
the duration of concurrent execution between synchronization points. We
then discuss use of the technique to predict the behavior of a dining phi-
losophers program on the ZMob distributed computer. Finally, we explain why
knowledge of periodic equilibrium behavior is important in programming dis-
tributed programs.

              GRAPHICS SEMINAR, Wednesday, May 6, 2 pm, GB120

                          Professor David Zeltzer
                   Massachusetts Institute of Technology

                          ``Motor problem solving
                                    for
                   three dimensional computer animation"

     In the recent past we have seen great  improvements  in the  ability
to  generate  and  display  complex  synthetic imagery.  Near-photographic
realism can now be achieved  for certain  classes of objects and
landscapes. However, current computer animation systems require far too
much technical or programming  experience on the part of the user, so that
the power of computer-based simulation  and  animation  is  gen- erally
unavailable  to  professionals who could make use of such tools for educa-
tion, design and research.  I argue that this  is not simply a user inter-
face issue.  Rather, we need to incorporate a rich representation of the
task domain,  so that  users  can  describe  an animated sequence as a set
of events  and  relationships  involving  the  characters   and objects in
a scene. I call this TASK LEVEL animation.

     However, even the simplest scenes and actions involving moving  fig-
ures  can  require  solving  a  host of seemingly trivial difficulties. All
kinds of animals as well as  human beings  have the capacity to move and
function in the physi- cal world efficiently, in the face of  changing
conditions, apparently without conscious intervention.

     A fundamental problem of task level  animation,  there- fore,  is  to
simulate the routine and stereotypical -- yet higly  adaptive  --
behaviors   of   agents   in   virtual microworlds.   I  describe a theory
of MOTOR PROBLEM SOLVING for task level animation of  human  and  animal
figures  in simulated  environments.   I  propose that a simple but very
general problem solving capacity is innate in the  organiza- tion  of an
agent's behavior repertoire, using a strategy of local means-ends analysis
for  forward-chaining  through  a lattice of motor skills without back-
tracking.  The domain of this problem solving paradigm is characterized, we
describe its  failure  modes,  and  suggest  that  advice-taking  and
mechanisms of attention and graded recruitment of  resources are plausible
means of recovery from failure.
-- 

Jim Clarke -- Dept. of Computer Science, Univ. of Toronto, Canada M5S 1A4
              (416) 978-4058
{allegra,cornell,decvax,linus,utzoo}!utcsri!clarke