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FORMALIZATION OF STRIPS IN
SITUATION CALCULUS
John McCarthy
Computer Science Department
Stanford University
Stanford, CA 94305
jmc@cs.stanford.edu
http://www-formal.stanford.edu/jmc/
2002 Oct 26, 3:00 p.m.
Abstract
[This is a 1985 note with modernized typography.]
STRIPS [FN71] is a planning system that uses logical formulas to repre-
sent information about a state. Each action has a precondition, an add list
and a delete list. When an action is considered, it is first determined whether
its precondition is satisfied. This can be done by a theorem prover, but my
understanding is that the preconditions actually used are simple enough that
whether one is true doesn’t require substantial theorem proving. If the pre-
condition isn’t met, then another action must be tried. If the precondition
is met, then then sentences on the delete list are deleted from the database
and sentences on the add list are added to it. STRIPS was considered to
be an improvement on earlier systems [Gre69] using the situation calculus,
because these earlier systems ran too slowly.
It was often said that STRIPS was just a specialization of the situation
calculus that ran faster. However, it wasn’t easy to see how to model a
system with delete lists in the situation calculus. In this paper we present
a situation calculus formalization of a version of STRIPS. Whether it is the
full STRIPS isn’t entirely clear. The reader will notice that a large amount
of reification is done.
We have situations denoted by s sometimes with subscripts. The initial
situation is often called s0. We also have proposition variables p and q
sometimes with subscripts. Associated with each situation is a database
of propositions, and this gives us the wff db(p, s)
asserting that p is in the
database associated with s. We action variables a, possibly subscripted, and
have the function result, where s(cid:48)
= result(a, s)
is the situation that results
when action a is performed in situation s.
STRIPS is characterized by three predicates.
precondition(a, s)
is true provided action a can be performed in situation
deleted(p, a, s)
is true if proposition p is to be deleted when action a is
add(p, a, s)
is true if proposition p is to be added when action a is per-
s.
performed in situation s.
formed in situation s.
STRIPS has the single axiom
∀p a s.db(p, result(a, s))
≡ if ¬precondition(a, s)
then db(p, s)
else db(p, s)
∧ ¬deleted(p, a, s)
∨ add(p, a, s)
.
We now give an example of this use of STRIPS in the blocks world. Our
individual variables x, y and z range over blocks. The constant blocks used
in the example are a, b, c, d and T able. The one kind of proposition is on(x, y)
asserting that block x is on block y. The one kind of action is move(x, y)
denoting the act of moving block x on top of block y. We assume the blocks
are all different, i.e.
U N A(a, b, c, d, T able)
We will be interested in an initial situation s0 characterized by
∀xy.db(on(x, y), s0)
≡ (x = a∧y = b)∨(x = b∧y = c)∨(x = c∧y = T able)∨(x = d∧y = T able).Next we characterize the predicates precondition, delete and add. We have
∀xys.precondition(move(x, y), s)
≡ x (cid:54)= T able ∧ x (cid:54)= y ∧ ∀z.¬db(on(z, x), s)
∧ (y (cid:54)= T able ⊃ ∀z.¬db(on(z, y), s)
),∀xys.deleted(on(w, z), move(x, y), s)
≡ w = x ∧ z (cid:54)= y
and
∀xys.add(on(w, z), move(x, y), s)
≡ w = x ∧ z = y.
From these axioms and the initial conditions given above we can prove
∀xy.db(on(x, y)
, result(move(a, b)
,
result(move(b, c)
,
result(move(c, d)
,
≡ (x = a ∧ y = b) ∨ (x = b ∧ y = c) ∨ (x = c ∧ y = d) ∨ (x = d ∧ y = T able).result(move(b, T able),
result(move(a, T able), s0))))))
Remarks:
sitions. Such a logic can be given by introducing an additional predicate
holds(p, s)
and the axiom
db(p, s)
→ holds(p, s)
together with axioms like
holds(pandq, s)
≡ holds(p, s)
∧ holds(q, s)
and
holds(not p, s) ≡ ¬holds(p, s)
.
We can then express preconditions in terms of what holds and not merely
what is in the database. However, holds(p, s)
will only be very powerful if the
propositions can contain quantifiers. This raises some difficulties which we
don’t want to treat in this note but which are discussed in [McC79]. Keep-
ing holds(p, s)
conceptually separate from db(p, s)
means that what holds is
updated each time the situation changes.
For this reason there is no difficulty in determining what remains true when
a proposition is deleted (or rather what propositions are true in result(a, s)
).
ple, we might have clear(x)
defined by
∀xs.db(clear x, s) ≡ ∀y.¬db(on(y, x), s)
and when move(w, z)
occurs with w (cid:54)= x and z (cid:54)= x, we would like to avoid
recomputing clear x. Obviously this can be done.
serve complete knowledge about the situation resulting from moving blocks.
The role of non-monotonic reasoning in these simple situations needs to be
studied. Compare [McC86].
intended meaning. For example, holds(p, s)
and holds(not p, s) are consistent
unless we have an axiom forbidding it, e.g. ∀ps.holds(p, s)
≡ ¬holds(notp, s)
.
This axiom may be stronger than we want, because it may be convenient to
use an interpretation of holds in which neither holds(p, s)
nor holds(notp, s)
is true.
because unless the proposition is deleted when its truth value changes, it can
lead to inconsistency when an action is performed. This instability is a de-
fect of STRIPS and other systems in which updating is performed by other
means than deduction.
also apply to linear logic and Wolfgang Bibel’s formalism TR.]
References
[FN71] R. E. Fikes and N. J. Nilsson. Strips: A new approach to the appli-
cation of theorem proving to problem solving. Artificial Intelligence,
2:189–208, 1971.
[Gre69] C. Green. Applications of theorem proving to problem solving. In
Proceedings IJCAI 69, pages 219–240, 1969.
[Lif87] Vladimir Lifschitz. On the semantics of strips. In Michael Georgeff
and Amy Lansky, editors, Reasoning about Actions and Plans.
Morgan-Kaufmann, 1987. reprinted in Readings in Planning Allen,
Handler and Tate (eds.), Morgan-Kaufmann, 1990.
[McC79] John McCarthy. First Order Theories of Individual Concepts and
Propositions1. In Donald Michie, editor, Machine Intelligence, vol-
ume 9. Edinburgh University Press, Edinburgh, 1979. Reprinted in
[McC90].
[McC86] John McCarthy. Applications of Circumscription to Formaliz-
ing Common Sense Knowledge2. Artificial Intelligence, 28:89–116,
1986. Reprinted in [McC90].
[McC90] John McCarthy. Formalizing Common Sense: Papers by John Mc-
Carthy. Ablex Publishing Corporation, 1990.
/@steam.stanford.edu:/u/jmc/w85/strips.tex: begun Thu Oct 16 11:35:32 1997, latexed October 26, 2002 at 3:00 p.m.
1http://www-formal.stanford.edu/jmc/concepts.html
2http://www-formal.stanford.edu/jmc/applications.html