gary@rochester.UUCP (10/14/84)
From: Gary Cottrell <gary>
The careful reader will have noticed that the default rule in the previous
announcement was upside down. The following announcement corrects the error.
University of Cottage Street
Dept. of Dog Science
55 Cottage Street
Rochester, New York 14608
SEMINAR
Saturday, 20 October, 1984
55 Cottage St.
9:00 p.m.
_M_o_d_e_l_l_i_n_g _t_h_e _I_n_t_e_n_t_i_o_n_a_l _B_e_h_a_v_i_o_r _o_f _t_h_e _D_o_g
Garrison W. Cottrell
Many of us, while out for a stroll, have had the
experience of observing a dog trotting along, alone,
obviously _g_o_i_n_g _s_o_m_e_w_h_e_r_e. This raises many questions, such
as, "Where is he going?", "Why is he going there?", "Will it
be more fun than where I'm going?", and so forth. Such
questions motivate us to postulate the existence of (and
hence the efficacy of further study of) the intentional
behavior of the dog[1].
We propose a highly parallel, neurologically plausible
model of dog behavior based on a connectionist (neural
network) implementation of a subset of Reiter's (1980)
Default Logic, as reported in Cottrell (1984). As outlined
in that paper, there is a well specified mapping of default
rules to connectionist network fragments that implement
those rules, with the benefit that the network operates in
real time by continuously updating the truth value of all
predicates in parallel[2] (thus making Doyle's work, and
perhaps Doyle himself, superfluous). Currently, the
implementation only allows inference rules with one
universally quantified variable. While inadequate for many
purposes, we claim that this is all we need for dog
modelling, since it appears that dogs can only think about
one thing at a time anyway[3]. In this work we reinterpret
____________________
[1]Grembowitz (1982) proposed a model of the cat, but
only handled the case of the cat tripping on catnip, cata-
tonically staring at the wallpaper for hours with sporadic
leaps into space. This simple behavior was elegantly
modeled by the composition of only two standard UNIX calls,
random(3c) and sleep(1).
[2]The observant reader will recognize a certain similar-
ity to British Motor Corporation's oft-lamented experiment
of shoehorning an Austin Healey six cylinder engine into an
MGB. Early results support the contention that our bastard
child of a similar "marriage made in hell" will be more suc-
cessful.
[3]It is interesting to note that the set of things a dog
can think about as noted in "Dog: A Canine Architecture",
Cottrell (1981) may be _f_i_n_i_t_e and limited to food, squir-
rels, and other dogs. Further, the dog we have studied ap-
pears to only have three responses to other dogs, depending
on their sex.
Reiter's default inference rules as precondition-action
behavior rules. An example behavioral rule is:
Moving(x) : Squirrel(x)
-----------------------
Chase(x)
An English interpretation of this rule is, "if
something is moving, and we don't have evidence that it
isn't a squirrel, then chase it." This models the observed
behavior of Jelly Bean chasing a paper bag. The real time
behavior of our implementation captures his stopping when it
turns out not to be a squirrel, since that blocks the
inference of Chase(x), which then slowly decays, much as
Jelly Bean slows to a confused halt. (As a simplifying
assumption, we ignore his subsequent pretense of not having
been chasing it at all.) Of course, we still have to
determine whether there might still be some peanut butter
and jelly in the bag, but this can be easily handled by the
addition of more rules. Note that since we are building a
model of behavior, the consequent of the rule is an action
(Chase(x)), not an addition of the useless information
Squirrel(x) to the already overtaxed knowledge base[4].
We have a grandiose long term research plan to model
the entire mind of the dog, which will generate grant
proposals _a_d _n_a_u_s_e_u_m. One of the new tools we plan to use
in this research is the previously unnoticed ability to
access the goal structures of the dog through measurement of
tail wagging (for a discussion of some other aspects of tail
wagging, including tail recursion, see "The Dog Papers",
Benson & Sloan (1984)). We claim that tail wagging will do
for dog modelling research what reaction times have done for
psychology. For example, we can use this technique to
assess the goal priorities of the dog. If we ask "do you
want to go out?" we get a vigorous wagging response, whereas
if we ask, "do you want to stay?", we get no tail wagging.
Further, we can map out all of the levels of the system by
studying the _t_i_m_e _c_o_u_r_s_e of the wagging behavior.
Demonstrations of the the time course of the wagging
response will be provided.
____________________
[4]As evidence that the knowledge base is already full,
one only needs to note that when Squirrel(x) holds, and x
climbs a tree, the dog repeatedly attempts to climb the tree
by jumping on the trunk, even though this tactic has never
been observed to succeed.