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Business
MIT
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MIT
Sloan School of Management
Sloan Working Paper 4187-01
eBusiness@MIT Working Paper 113
October 2001
A DECLARATIVE APPROACH TO BUSINESS RULES IN
CONTRACTS: COURTEOUS LOGIC PROGRAMS IN XML
Benjamin Grosof, Yannis Labrou, Hoi Y. Chan
This paper
is
available through the Center for
eBusiness@MIT web
site at the
following
URL:
http://ebusiness.mit.edu/research/papers.html
This paper also can be downloaded without charge from the
Social Science Research
Network Electronic Paper Collection:
94
http://papers.ssm. com/abstract_id=2 9
A
Declarative Approach to Business Rules in Contracts:
*
Courteous Logic Programs in
XML
IBM
T.J.
Benjamin N. Grosof
Watson Research Center, P.O. Box 704, Yorktown Heights, NY 10598,
grosof@us ibm. com (alt.: grosof @cs .Stanford, edu)
USA
.
http //www research ibm. com/people/g/grosof
.
:
.
Yannis Labrou
Computer Science and
Electrical Engineering
and Department
21250, USA
University of Maryland, Baltimore County, Baltimore,
klabrouOcs
MD
edu
http //www. cs .umbo edu/~ jklabrou/
j
.
T.J.
.
.
:
IBM
urnbc
Hoi Y. Chan
Watson Research Center, RO. Box 704, Yorktown Heights,
NY
USA
10598,
hychanOus ibm com
.
.
Abstract
forms any
CLP
into a semantically equivalent
OLP
with moderate, tractable computational overhead.
We
address why, and especially how, to represent
business rules
e-commerce
in
we mean
tracts,
By
contracts.
Second,
con-
suitable
offered or sought, including ancillary agreements
detailmg tenris of a deal.
We
sions,
observe that rules
We
such
& conditions, service provi-
contracts.
in
The
interchange between heterogeneous
BRML
can also ex-
Knowledge
In-
Our new approach, unlike previous approaches,
provides not only declaratives emantics but also
with several examples.
rules
for
terchange Format (KIF) which overlaps with CLP,
prioritized conflict handling, ease of parsing, and
analyze requirements (desiderata) for repre-
senting
new XML encoding of CLP,
Markup Language (BRML),
press a broad subseto f ANSI-draft
and surrounding business processes, and we
illustrate this point
give a
commercial rule languages.
are useful in contracts to represent conditional rela-
tionships, e.g., in terms
we
called Business Rules
descriptions of goods and services
integration into
require-
ments mclude: declarative semantics so as
ing.
to en-
We
WWW-world
argue that
this
software engineer-
new approach meets
the
able shared understanding and interoperability; pri-
overall requirements to a greater extent than any
modu-
of the previous approaches, including than KIF, the
oritized conflict handling so as to enable
lar updating/revision;
into
WWW-world
leading previous declarative approach.
ease of parsing; integration
We
software engineering; directe x-
have implemented both aspects of our ap-
ecutabihty; and computational tractability.
proach; a free alpha prototype called
We
Rules was released on the
give a representational approach that consists
of two novel aspects.
First,
we
give a
new
in July
Commonof 1999,
at
http //alphaworks ibm. com.
fun-
damental knowledge representation formalism:
Web
.
:
An
a
generalized version of Courteous Logic Programs
extended version of
this
paper will be avail-
IBM Research Report
http //www. research ibm. com).
able as afo rthcoming
(CLP), which expressively extends declarative or-
:
(at
.
dinary logic programs (OLP) to include prioritized
conflict handling, thus enabling modularity in spec-
ifying
and revising
plementing
CLP
is
rule-sets.
a
Our approach
1
to im-
courteous compiler that trans-
One form of commerce
Copyright
ACM. To appear:
Proceedings
of the
1st
Conference on
Electronic
Commerce (EC99),
to be held Denver,
3-5,
Colorado, USA, Nov.
1999.
Edited by Michael R Wellman.
New York, NY:
ACM
ACM
Press,
1999.
http://www.ibm.com/iac/ec99/
hccp; //www. acm.org.
Introduction
or
automation
is
that
could benefit substantially from
contracting,wh ere agents form binding.a gree-
able terms, and then execute these terms.
mean
initially parties in the
Economics
By
"agents",
we
sense, e.g., as buyers
or sellers; however, once automated, these agents might be
intelligent agents in the
Computer Science
sense.
agreements, delivery schedules, conditions for returns, usage
we make a sharp distinction between the repremechanism for communicating contract rules, and
the actual rule execution mechanisms employed by participating agents. Our concern here is with the former, though of
course in designing a communication mechanism one must
good or service
consider and anticipate the requirements of execution to be
By e-commerce
scriptions
we mean
"contracts",
broad sense: de-
in a
otgoods and services offered or sought, along with
&
applicable terms
of
tailing teniis
conditions,
a deal.
i.e.,
ancillary agreements de-
Such terms include customer service
and other issues relevant
restrictions,
to the
Such descriptions are
fronts, as well as in bids
to
be found
in
We
catalogs and store-
and requests communicated
by
(e.g.,
agents) during negotiations, procurements, and auctions.
overall contracting process comprises several stages,
Discovery: Agents find potential contracting partners.
approach
will take a declarative
By
contracts.
to business rules in
"declarative" semantics for rules,
we mean
sense of knowledge representation (KR) theory,
in the
including broadly:
1
that
performed by each of the agents.
provided.
The
Note
sentational
in
a
manner abstracted away from the choice ofim plementation
approach: the semantics say which conclusions are entailed
model-theoretically) by a given set of premises, with-
(e.g.,
out dependence on procedural or control aspects of inference
2.
Negotiation:
Contract terms are detemiined through a
process of communication between agents, often involving iterative modification of the contract terms.
3.
Execution:
We
observe that
many
is
used
to
mean any kind of
By
significant ap-
computing an
(i.e.,
the IF part)
(i.e.,
AND'ed)
we mean more
"rule" in this paper,
specifically an implication
(i.e.,
may
IF-THEN)
rules, of-
(Sometimes,
plication logic, e.g., the algebraic formula for
insurance annuity.
Example Roles for Rules
Conflict Handling
contract terms involve conditional
ten called business nileso r business policies.
tecedent
is
backward
versus forward.
2
and can conveniently be expressed as
"business rule"
from whether the direction of rule inferencing
Transactions and other contract provisions
are executed by the agents.
relationships,
away
algorithms. In particular, declarative semantics abstract
in
which the an-
contain multiple conjoined
Next,
we
and Prioritized
give a few brief examples, expressed
As we
guage, of business rules in contracts.
in natural lan-
go,
conflict,
and the opportunity
— because of
Example
A
typical
we
will see
— because of
both the need for prioritized conflict handling
for prioritized conflict handling
naturally available prioritization information.
(Refund Policy)
1
example of a
seller's
refund policy
is:
conditions.)
For example, rules are useful
• (Rule A:) "If buyer returns the purchased
in describing:
good
any
for
reason, within 30 days, then the purchase amount, minus
• terms
&
conditions, e.g., rules for price discounting;
•
surrounding business processes,
to place
10%
a
• service provisions, e.g., rules for refunds; and
lead time
is
an order.
defective, within
will
We
believe that
B
Rule
many
fiinded".
in
automated
contracts.
In this
Here,
work we
are concerned primarily with the negotia-
tion stage of contracting,
and specifically with how
to repreit
sent business rules in contracts.
The contract terms may or may not be modified during
may be
tance. Crucial during negotiation, however,
tract
the
a rel-
communication followed by accep-
must understand and agree.
In
is
thatal
1
(More
year, then the full purchase
"If both Rules
i.e.,
say a rule "applies"
is
satisfied.
The
when
30 days.
In this case,
a
common
generally,
body
be
(i.e.,
re-
an-
necessary because
Rules
A
and B
it
is
de-
conflict
incompatible with each other. The conflict
ority:
Rule
B
is
is
resolved by pri-
specified to have higher priority than Rule A.
agents
some agents might
the scope of this paper.)
a shared language with
understanding of rules
which agents can reach
in contracts,
rules are relatively easily modifiable,
executable by the agents.
is
will
with each other; both rules apply but their consequents are
Example
2
(Lead Time)
In business-to-business
commerce,
minimum advance
beyond
amount
can happen that the buyer returns the good because
man
is
and B apply, then
that rule's
Priority Rule
be human, as well as automatic; however, the aspects of hu-
Our goal
A
the full purchase
supply chains, sellers often specify
interaction are
it
amount
terms of automation, the con-
has to be communicated and digested by each agent,
with shared semantics.
'wins',
fective within
negotiation stage. If not, the negotiation stage
atively simple process of
we
tecedent)
I
be refunded."
• (Priority Rule:)
rules as an overall representational approach capture well
aspects of what one would like to describe
good because
• (Rule B:) "If buyer returns the purchased
e.g., rules for
(Section 2 elaborates on these examples.)
restocking fee, will be refunded."
such that the
communicatable, and
e.g.,
in
manufacturing
how much
lead time,
required in order to place or modify a purchase order.
example of a parts supplier vendor's lead time policy
•
(Rule A:) "14 days lead time
customer."
i.e.,
notice before scheduled delivery date,
if
the buyer
is
is
An
is:
a preferred
• (Rule B:) "30 days lead time
minor
backlogged
is
the ordered item's itein-
it":
vendor, and the order
at the
is
a
'wins',
"II'
sponding bids, often involve conditional relationships
A
Rules
between price, quantity, and delivery date, e.g., "If
is between 400 and 1000 units, and
and C both apply, then Rule
pleased to have
IS
Rules A, B, and
appK
the order quantity
C
flict
more
is
ever, the
having trouble
m
the
product catalogs, many properties of a product
are
above
between them
when
information -
more
•
its
In
ties
at
how
modem".
XS,
able in sizes
con-
common
of that product, rather than being particular
internal
How-
to resolve
E.g., "all
V-neck sweaters
and black".
are available in fabrics acrylic
authorization are often naturally expressed
Example 3 (Bookstore Personalized Discounting)
sufficient and/or necessary conditions.
today
among e-commerce
A
and
• Policies about creditworthiness, trustworthiness,
priority to resolve all potential conflicts.
interest
in-
and cashmere".
moment during the process of
may be insufficient justified
Sellers often provide personalized price discounting.
an
women's T-shirts are availM, and L", "all men's T-shirts are
M, L, XL, and XXL", and "all T-
shirts are available in colors navy, khaki,
sit-
incremental specification, there
of considerable
to
E.g., "all
S,
available in sizes S,
B, for example; no relative priority
any given
unit.".
dividual product. E.g., "all laptop computers include an
accumulate over time, or are specified by
rules
multiple authors:
and 30 daysfro
most naturally specified as conditional on other proper-
rationale might be that
recent, than Rule A.
specified as yet. This reflects a
is
15
$48 per
is
buyers) for the item, and
rule-set leaves unspecified
A and
between
is
order date, then the price
two or three of them might
conflict:
specific, or
between Rules
uation
is
buyer relieve the pressure.
this
C may
all its
vendor
given purchase order. The Priority Rule provides
to a
partial prioritization
Rule
that the
is
orders (from
filling its overall
thus
C
AAA
example above
• In supply chain settings: requests for proposals, and re-
the delivery date
The
hotel discounts for
in feel to the
about personalized discounting.
mod-
days lead time,"
i.e. ,2
rationale for Rule
e.g.,
members, are often similar
a preferred customer."
• (Prioriis Rule:)
C
about discounting for groups or preferred
• Policies
a
reduce the quantity of the item, and the buyer
ification to
is
is
customer organizations,
• (Rule C:) "2 days lead time
type
the ordered item
if
part."
in
terms of
Such conditions
include: credentials, e.g., credit ratings or professional
topic
certifications; third-party
sellers
recommendations; properties
is
of a transaction
how to do this more cheaply and uniformly by automating it.
An e.xample of a bookstore's personalized discounting policy
in question, e.g., its size or
mode of pay-
ment; and historical experience between the agents,
e.g.,
familiarity or satisfaction.
is:
• (Rule A:) "5 percent discount if buyer has a history of
loyal spending at the store."
•
(Rule B:) "10 percent discountif buyer has a history of
big spending at the store."
Rule Representations: Previous Approaches
including KIF, Requirements Analysis
In section
(Rule D:) "10 percent discount
if
buyer
is
a
member of
standing of rules
• (Rule E:)
"No
discountif buyer has a late-payment his-
tory during the last year."
(Priority Rules:)
is
"B
is
A
and than
C
A
all
and than C; E
the othis
higher
Here, the Priority Rules specify a set of priority comparisons,
(i.e.,
among
the rules.
many
underre rela-
communicatable, and executable
analyze and elaborate these require-
for Rules
contract terms can be well represented
We
tion for our approach.
begin by reviewing previous ap-
proaches.
mented commercial use
erally (not for contracts in particular).
code constructs
in
programming languages such
is
Prolog
[3], a
lated to Prolog,
is
SQL
One approach
is
as C,
C++, and
rules.
A
rules.
views. In
di-
Java'.
second ap-
programming language oriented
to-
A third approach, closely reSQL-type
• Policies about cancelling orders are often similar in feel
examples above about refunds and lead time.
wide imple-
general-purpose imper-
Other approaches are more specific to
proach
in
for representing business rules gen-
wards backward-chaining
as rules.
to the
which we bold-face
desiderata,
or
throughout this section) for a rule representation, and discuss
ative
believe that
we
criteria
rectly as if-then
More Example Roles
a shared
such that the rulesa
There are multiple approaches already
and than D."
that are sufficient to resolve all the potential conflicts
We
in contracts,
is
common
candidate previous approaches in light of them, as motiva-
higher priority than
higher priority than
priority than
work our goal
by the agents.
ments
D
stated that in this
In this section,
the store's Platinum Club."
ers;
we
tively easily modifiable,
card."
•
1,
language with which agents can reach a
• (Rule C:) "5 percent discount if buyer has a store charge
•
3
'trademark of Sun Microsystems Inc.
relational database
systems [22] a view
is
coiiJiiion-action rules
kind found
to
"active rules"
I
SQL
views,
is
eveni-
"triggers" [22] of the
/
many database systems and
in
A
defined, in eflect, by a set of rules.
approach, fairly closely related
fourtli
routing systems.
These are forward-directed, triggered by events such as updating a database relation. A fifth approach is production
rules, a
form of forward-chaining
approaches as well,
e.g., in
of the kind
rules,
0PS5 system
tems descended from the
[4].
in sys-
There are other
expert systems, knowledge-based
systems, and intelligent agent building tools, but the above-
probably the currently most commercially impor-
listed are
tant, especially
A
m
e-commerce.
approach
sixth
edge Interchange Format (KIF)^. KJF
Rather,
is
KIF
Knowl-
not a directly ex-
language for
a
is
is
in-
terchange of knowledge, including rules, between heteroge-
neous software systems,
convenience
convenience
More
e.g., agents.
precisely,
a prefix' version of first-order predicate calculus
An
important aspect of expressive power
i.e.,
rules that
KIF
is
(i.e., first-
in several other
munication,
e.g.,
is
IF,
cur-
standards committee process.
is
also being considered infor-
standards efforts relevant to agent
FIPA^'.K
however,
not yet
is
com-
wide im-
in
plemented commercial use.
Next,
we
One group of requirements
revolves
the ability to
is
are default rules.
important to conveniently express pri-
oritized conflict handling,
where some
i.e.,
rules are sub-
by higher-priority conflicting rules, such as
by special-case exceptions, by more-recent updates, or by
examples
As we saw
in
our contract rule-set
and the need/opportunity
in section 2, conflict,
for
prioritized override, frequently arise.
Most commercially important
rule systems (including the
above-listed widely implemented approaches)
monotonic reasoning as an
employ non-
highly-used feature.
essential,
employ some form of negation-as-failure. Ofemploy some forni of prioritized override between
e.g., the static rule sequence in Prolog or the computed
Typically, they
rule-activation sequence/"agenda" in 0PS5-heritage production rule systems.
modern software
In
vital aspect
design,
is
it
widely recognized that a
of modifiability ismod ularity and locality in
revision, e.g., in the
manner
itized conflict
cation and
and informa-
that subclassing
tion hiding provide in object-oriented
elaborate on requirements and relate them to the
previous approaches.
is
it
ject to override
rules,
KJF
of classical higher-order logic) and definitions.
mally
employ negation-as-failure or
In particular,
operator (thus enabling additional expressiveness akin to that
Supporting or endorsing KIF
process of specification. Expressive
an aspect of expressive power, but also
conveniently express rules that are logically non-monotonic,
ten they
ANSI
for the
in part
implies the need for conceptual naturalness of semantics.
order classical logic) with extensions to support the "quote"
rently well along in the
is
higher-authority sources.
for representing business rules
ecutable representation.
Ease of modifiability implies the requirement of expressive
programming.
Prior-
handling enables significantly easier modifi-
more modular revision/updating.
New
behavior
around heterogeneity. Specifically, the multiplicity of widely
can be specified more often by simply adding rules, without
implemented approaches implies an immediate requirement
needing
to
cope with heterogeneity of implementations of busi-
ness rules.
The
communicate with shared under-
ability to
standing then implies the requirements of interoperability
to
modify the previous
ous general-case
case rule.
This
rule,
is
with declarative semantics. The above-listed widely imple-
in object-oriented
mented approaches lack
needing
fully declarative semantics.
Communicatability and interoperability imply the require-
ment of ease of parsing
Interoperability
cated.
rule-sets that are being
and
practical executability
requirement of integration into
gineering overall. The
tates
A
XML
WWW-world
communiimply the
software en-
aspect of ourapp roach
facili-
overall requirement
more
is
expressive power
in
specific-
to
modify
without needing to modify the general-
similar to the modular/local gracefulness
programming of adding
a subclass without
the superclass.
Another important aspect of expressive power,
tion to practical executability,
is
in
rela-
the ability to conveniently
express procedural attachments.
Procedural attachments
are the association of procedure calls with belief expres-
Example
sions, e.g., in
1,
the association of the Java
.
second group of requirements revolves around expres-
A basic
E.g., a
CustomerAccount setCredi tAmount
such parsing and integration.
siveness.
rules.
case rule can be added and given higher-priority than a previ-
cal predicate
refund. Procedural attachments
method
with the logiare crucial in
order for rules to have actual effect beyond pure-belief in-
specifying rules. Practical executability, however, implies the
ferencing, e.g., forac tions to be invoked/performed as a re-
strong desire for computational tractability in the sense of
sult after rule
Expressive power
average-case and worst-case complexity.
to
listed
^http //logic Stanford. edu/kif /
and
http //www. cs umbo .edu/kif/
^The
specification
current
draft
ANSI
of
KIF
(http //logic Stanford. edu/kif /dpans .html) also
Procedural attach-
invoke procedure calls when
rule conditions are tested/queried.
has to be balanced against tractability.
Almost
all
of the above-
widely implemented approaches include procedural
at-
.
:
tachments.
.
:
.
:
includes an infix version of
KIF intended
automated exchange.
"Foundation
for
Intelligent
for
human consumption
rather than
http //www
:
conclusions are inferred.
ments are also very useful
.
f ipa
.
org
Physical
Agents:
However, procedural attachments are semantical ly probis how to give them
lematic, and an open research issue today
a semantics that abstracts
and
is
away from implementation
details
thus akin to being declarative. (See the discussion of
Situated Logic Programs in section 5.)
com-
we have here
further expressively generalized, notably to han-
response to the need to cope with implemen-
dle pairwise
mutual exclusion
K.IF has been developed specifically for puqioses of
munication,
in
tational heterogeneity
of rules and other knowledge. By con-
with the abo\e-listed widely implemented approaches,
trast
KIF has
a fully declarative
intended strength.
Its
is
4.1
We
and compu-
logically monotonic, highly expressive,
is
is its
focusing on first-order logic. First-order
sical logic, primarily
logic
main
based on clas-
semantics; indeed, that
declarative semantics
perform inferencing) for the general
tationally intractable (to
case
a
broad class of
rules.
However,
it
has
several important shortcomings as a language for business
rules in
e-commerce, including
KIF has
crucially,
a
Perhapsm
in contracts.
shortcoming of
edge representation (KR):
KR
tal
its
fault rules,
and prioritized conflict handling;KI F
logically
is
monotonic. KIF also cannot (conveniently) express proceduattachments;
it
a pure-belief
is
KR. KIF has been designed
with an orientation towards knowledge as a non-executable
specification as
ecutable. Also,
much or more than towards knowledge as exthe KIF effort has focused more on a highly
inclusively expressive representation than
thing the
XML aspect of our approach
This
for rules to be: declarative
is
some-
Ordinary Logic Programs
[23], inhially
we will leave "declarative" implicit.)
KR, i.e., it lacks procedural attach-
(Henceforth,
a "pure-belief"
is
ments.
Each
Here,
OLP
rule in an
<-
Ao
n >
m
Ai
>
has the form:
/\
.
.
h
.
Am
and each A,
0,
~^m+l A
/\
A ~An.
...
Aq
a logical atom.
is
called
is
head (i.e., consequent) of the rule; the rest is called
body (i.e., antecedent) of the rule. If the body is empty,
the
may
<—
and
is
A
be omitted.
~
a fact.
ground
empty body
rule with
the
the
called
is
stands for the negation-as-failure operator symbol,
read in English as "fail". Intuitively,
not believed to be true,
is
i.e.,
~p means
that p's truth value
that
p
either
is
false or unknown.
on ease of develop-
ing translators in and out of that representation (this
Ordinary Logic Programs
expressively restricted to the predicate-acyclic case (defined
fundamental knowl-
cannot (conveniently) express
it
KR Step:
(OLP), with the well-founded semantics (WFS)
ost
logical non-monotonicity, including negation-as-failure, de-
ral
First
simply
conflicts, rather than
-ip.
begin defining our approach by choosing the fundamen-
below).
KIF can express
form p versus
conflicts of the
Example 2 might be
E.g., the first rule in
written as:
order Modi ficationNotice{'?Order, day sli)
improves upon).
pre ferredCustomerO f {? Buyer ISeller)
<—
,
A purchaseOrderClOrder, ? Buyer, ? Seller)
our
In
none of the above-listed previous approaches
\ievv.
to representing business rules,
proach that
we
are
aware
of requirements we
of, satisfactorily
listed
above
Here, the prefix "?" indicates a logical variable.
Ordinary LP's have been well-studied, and have a large
nor any other previous ap-
meets the whole
set
(in bold-face). In particular,
lit-
erature (reviewed, for example, in [I]). For several broad but
restricted expressive cases, their (declarative) semantics
is
un-
the widely-implemented approaches above lack sufficiently
controversial: e.g., for the predicate-acyclic, stratified, locally
declarative semantics; KIF, though declarative, lacks logical
stratified,
non-monotonicity.
increasing expressive generality. However,
KIF's declarative approach does, however, inspire us
velop our
own
to de-
and weakly
cursion" here
4
A New
Courteous Logic Programs +
The approach
—
in
to
is
choose Ordinary Logic Programs (OLP)
the declarative sense
Prolog
—
cretely in
XML
for
tionally efficient,
]
provides a helpful review), not
plus to
embody
this
KR con-
Logic programs are noton
ly relatively
ut also practical, relatively
computa-
and widely deployed.
KR
CLP
formalism
to
be Courteous Logic Programs
expressively extends Ordinary Logic Programs
to include prioritized conflict handling,
computational
tractability.
CLP
is a
that there is a cyclic (path
while maintaining
previous
KR
[10]
which
"Ordinary" logic programs are also sometimes known as "general" (e.g., in [1]) or "normal" logic programs, or as (the declarative
version of) "pure Prolog".
of
of syntactic)
more generally, among
the ground atoms) through rules. More precisely, a logic program S's predicate dependency graph PDGs is defined as
follows. The vertices of the graph are the predicates that appear
in S.
rule r in
acyclic"
£
is
{p,q)
with
means
p
that
a (directed)
(or,
edge
in
PDGs
iff there is a
head and q in its body. "Predicatethere are no cycles in the predicate depen-
in its
dency graph. "Stratified"
(in its various flavors)
means
cycles
of a restricted kind are allowed.
The well-founded semantics
expressively extend the approach's declarative fun-
damental
(CLP).
1
KR,
purposes of communication between the
'
powerful expressively,b
We
([
as a fundamental
contracting agents.
XML
series
of recursion with negation-as-failure. "Re-
means
dependency among the predicates
Declarative Approach to Rules:
form a
OLP's have prob-
lematic semantics for the unrestricted case, due essentially
to the interaction
declarative approach.
stratified cases; these
is
probably the currently most
popular semantics for the unrestricted case, and
vorite.
set
is
our
fa-
With WFS, the unrestricted case always has a single
of conclusions, and
strictions (e.g.,
Our approach
business rules
is
tractable under
commonly-met
re-
VBD defined below).
for an initial practically-oriented
KR
stricted cases that
is,
however,
to
keep
have uncontroversial
research community) semantics
—
LP-based
to expressively re-
(i.e.,
consensus
in the
starting with predicate-
Compared
acyclic.
uncontroversial cases, the unre-
to these
WFS)
more complex computationally and, perhaps even more importantly, is more difficult in
terms of software engineering, lireq uires more complicated
stricted case (e.g., with
algorithms and
is
and with relatively low computa-
atively simple algorithm
tional cost.
WFS)
(with
entails a set
consists of a set of premise rules, and
of (primitive) conclusions. In a predicate-acyclic
OLP, each conclusion has the form ofa ground atom. Intuitively, each conclusion atom is believed to be true, and every
other (i.e., non-conclusion) ground atom is not believed to be
(recall
we
Next,
1):
~
discuss the advantages of
OLP
OLP's (with WFS).
has a fully declarative semantics that
(Adv
use-
is
OLP
2):
in-
cludes negation-as-failure and thus supports basic logical
(Adv
non-monotonicity.
sive power, yet
sively.
(Adv
is
4):
OLP
3):
and
relatively simple
OLP, unlike
has considerable expresis
not overkill expres-
met expressive
restrictions, e.g.,
rule-set execution
—
polynomial-time.
Here,
it
is
in
the
non-/^ero arity (a.k.a.
VBD,
say that an
LP
is
in
is
Daialog
co-NP-hard under the
among many commercially
has a
it
VBD restriction.
is
— and thus
(Adv
5):
We
widely shared
important rule-based systems as
Prolog
is
the
most
obvious family of such systems. Relational databases are another such family;
many SQL view
algebra operations) are in effect
definitions (and relational
OLP
rules.
0PS5-heritage
production rule systems are less closely related because of
of procedural attachments, but insofar
their extensive use
commonly do
their semantics
pure-belief predicate-acyclic inferencis
closely related to forward-directed
OLP's. Event-condition-action rules are somewhat similar
this
adding the capability to conveniently ex-
in
regard to a simple form of production rules. Other sys-
tems sharing the semantics include many expert/knowledgebased systems and intelligent agent building tools;
many of
these implement forward-directed predicate-acyclic OLP's.
Predicate-acyclic
tational tractability (e.g.,
OLP
KR
a previous
is
semantics thus reflects a consensus
in
community that goes beyond the logic
programming community. (Adv 6); Predicate-acyclic OLP's
are, in effect, widely implemented and deployed, including in
Prolog's and SQL relational databases, but also beyond them.
the rule representation
[10]
under the
VBD
compu-
which we have here
further expres-
sively generalized, notably to handle pairw'ise
mutual exclu-
->
sus ->p. (Here,
CLP
is
a predicate
/p having anty
argument corresponds
fc -I-
1,
where
inUiitively the
(fe
to the resultof applying the flinction.
-|-
l)""
p
ver-
-p
stands for classical negation. Intuitively,
believed to be definitely false.)
can be tractably compiled to OLP. Indeed, we
have implemented such a courteous compiler [II] [13]
The compiler enables modularity
in
[12].
software engineering and
LP
ex-
pressive capability can be added modularly to an Ordinary
LP
eases implementation and deployment: the Courteous
pilation's computational
often
Com-
simply by adding a pre-processor.
rule engine/system
complexity
cubic, worst-case, but
is
closer to linear.
is
stead, here
we
we do
CLP
not have space to give
formalism or
will give an
details, see [12]
its
full details
about
courteous compiler. In-
overview and some examples. For
and the forthcoming extended version of this
paper.
CLP
handles
conflicts
between
rules
ordered prioritization information that
is
using
partially-
naturally available
based on relative specificity, recency, and authority. Rules are
subject to override by higher-priority conflicting rules.
example, some rules
may be
For
overridden by other rules that are
special-case exceptions, more-recent updates, or from higherauthority sources.
Courteous LP's
ing,
facilitate
specifying sets of rules by merg-
updating and accumulating, in a style closer (than Ordi-
nary LP's or than classical logic/KIF) to natural language descriptions.
The expressive extension provided by CLP
valuable especially because
is
thus
greatly facilitates incremental
to explicitly modwhen updating or merging. In terms of the
representation requirements we gave in section 3, this en-
specification,
ify
it
by often eliminating the need
previous rules
rule
ables significantly greater modularity, locality,ea se of modification.e xpressive convenience,
In
CLP,
labels:
override s{rulel, rule2) means
priority than rule2.
will
and conceptual naturalness.
priorities are represented via a fact
win the
If
that
rulel and rule2
comparing
rule
rulel has higher
conflict, then
rulel
conflict.
CLP rule differs from an OLP rule in two
may have an optional rule label, used as a
Syntactically, a
ways.
First,
it
handle for specifying prioritization. Second, each rule
usually straightforward to representationally refomiulate a
rule-set so as to replace a logical flinction / having arity fc >
by
"It is
CLP
restriction).
sion conflicts, rather than simply conflicts of the form
In this paper,
and
restriction^)
an expressive subset of their behavior.
ing,
WFS) by
(with
the generalized
''VBD" when
just
Courteous LP's (CLP) expressively extends Ordinary LP's
i.e.,
logical variables appearing in each rule.
observe predicate-acyclic OLP's semantics
as they
of developers (not
are familiar with them.
Programs
worst-case
has no logical fijnctions of
it
contrast, classical logic, e.g., first-order logic
KIF,
—
inferencing
can be computed
ground, or (b)
bounded number of
By
OLP
we
compuUnder commonly
first-order-logic/KIF,is
tationally tractable in the following sense.
either (a)
a large population
is
who
KR Extension to Courteous Logic
4.2
means p
above).
and well-understood theoretically.
ful
There
press prioritized conflict handling, while maintaining
An OLP
(.\dv
7):
researchers)
not widely deployed. The predicate-acyclic
is
expressive restnction can be checked syntactically with a rel-
true
(Adv
may be
classically negated.
specialca se of CLP.
An OLP
mention classical negation.
Syntactically,
OLP
rule lacks a label
is
literal
simply a
and does not
A CLP
rule has the fomi:
<-
Lo
{lab)
m
>
Here, n
sical literal
an atom.
and
The
The
label
.
is
The
.
A ~L„.
...
-i.4,
or
-4
English as "not", lab
A
clas-
where
.4 is
the rule's label.
is
optional. If omitted, the label
is
not required to be unique within the scope of the
label
is
treated as a
above have
may have
rules
all
the
tion
is
CLP entails a
a
ground
(b)
(c)
between p and
implicit mutual exclusion
In the
An
conflict.
±
order Modi ficationNotice{'?Order,?X) A
<—
e
CLP
{IX ^lY).
also op-
mutex 's specify
the
unconditional mutex has the syntactic
form-
±
is
a classical
Semantically, each such
literal.
mutual exclusion specified by a mutex
is
L2
enforced: Li and
instantiation).
These mu-
tex's are particularly useful for specifying that at
most one of
are never both concluded (for
a set of alternatives
is
to
any
be permitted. E.g.,
in
Example
1 ,
it
is
straightforward to specify via a mutex that the refund percent-
age must be
at
Example
it
2,
the lead time
most one of the values {90%
is
,
100%}.
at
E.g., in
example
while handling conflict appropriately
most one of the values {2 days, 14
Example 3, it is straightforward to
section
to
use a more
Semantically, the prioritized conflict handling
opposing candidates. Opposition
Each
mutex's.
is
rule r
?Z
I
(?y 7^?Z).
Li and ^2- E.g.,
giveDiscount[1Cust, lY Percent)
A giveDiscount{1Cust, ?Z Percent)
(lY Percent ^?ZPercent).
This conditional mutex enables one to specify with a single
mute.x statement (rather than with three or more unconditional
mutex's) that for a given customer ICust there must be at
most one value concluded for the discount percentage.
tively in
±
<—
I
The enforcement of
set
classical negation can be
viewed as
a
oi implicit unconditional mutex's, one for each predicate
CLP is
among
in
label. In general, there
i.e.,
p
is
the set of
which
i.e.,
is
label,
may
for
if
there
a candidate for an opposing
c,
then c
an unrefuted candidate for p.
concluded. However,
which
be multiple
a team for p. If and only
(i.e.,
no unrefuted candidates
fiited
satisfied,
q) that has higher priority than candidate
futed. Suppose there
i.e.,
by
specified
is
head p. This candidate has an associated
an opposing candidate d
are
in
candidate c for r's (appropriately instan-
simply that rule r's
literal
are logical variables that appear respec-
is
whose body
is
Li A L2
is
(recall
andea se of modification
defined by a process of prioritized argumentation
candidates for a given p,
and
This
3).
syntactic form:
^
more
and underscores the advantage
the discussion of modularity
general form of mutex: a conditional mutex, which has the
TV
modifying the
that prevent
of the prioritized conflict handling expressive feature
tiated)
more convenient sometimes
1
regard to priorities
add additional such interaction conditions.
typical of conflicting rule-sets
most one of the values {0%, 5%, 10%}.
where
in
requires
Moreover, adding a new rule requires modifying the other
rules to
"fires", generates a
expressively
—
add extra "interaction" conditions
specify via 3 mutex's that the discount percentage must be at
It is
LP
directly as an Ordinary
and guaranteeing consistency
E.g., in
straightforward to specify via 3 mutex 's that
must be
days, 30 days}.
this
than one rule applying to a given purchase order situation.
Li A L2.
t-
—
I
To represent
rules to
where each Lj
A
order ModijicationNotice{10rder, lY)
of pairwise mutual exclusion (mutex)
statements, along with the rules. These
'^Seller)
overrides{c,a).
-ip.
newly generalized version of CLP,th
tionally includes a set
scope of
any
as
preferredCustomerOfC? Buyer,? Seller) A
order ModificationType{? Order, reduce) A
orderltemi sInBacklogilOrder) A
purchaseOrder{? Order, 1 Buyer, ISeller).
<—
can be viewed as the enforcing of an
(classical literal) p. This
CLP
'?
Classical nega-
-^p are never both concluded, for
p and
enforced:
CLP)
in
purchaseOrder{'!Order, Buyer, ? Seller).
order Modi ficationNotice{?Order, days30)
(— minor Part{? Order) A
purchaseOrder{?Order, ? Buyer, ?Seller).
or derModificationNotice{1 Order, days2)
of (primitive) conclusions
set
Lead Time,
preferredCustomerOf{? Buyer,
<—
the
ground instances of
classical literal.
.
order Modi ficationNotice{?Order, dayslA)
(a)
program.
is
,
.
2 can be straightforwardly represented in
to other predicate and function symbols appearing in the logic
Semantically, a
.
follows:
treated as part of the language of the logic program, similarly
each of which
,
Example
overrides and the labels are
label lab.
.
4 (Ordering
same la0-ary function symbol. The label
two
i.e.,
.
.
arity is
Example
said to be empty.
is
is
Q(?X1,
IXni) A ^g(?Xl,
?Xm).
m. This is called a classical mutex.
<-
where Q's
a classical literal.
is
of the t'onn
preserved during instantiation;
the rule
1
stands for the classical negation operator symin
each have the form
that
.
and each I,
0,
overall logic program;
bel.
Q,
A Lm
A
A ~Lm+i A
a Ibniiula
read
is
label
>
is
->
bol,
Li
is re-
If there
any opposer of p, then p wins,
it
may
be that there
is
an unre-
candidate for an opposer of p; in this case, the opposing
unrefuted candidates skeptically defeat each other. The conflict
its
cannot be resolved by the specified priority; neither
opposer
is
Another way
locale
is
p nor
concluded.
to
a set of
view
/i
>
thisis
as follows.
2 ground classical
pose each other,su ch that
at
An
opposition-
literals that
most one of those
literals
mitted (by the specified mutex's) to be concluded.
is
opper-
In each
opposition-locale, if the maximal-priority candidates are
same
for the
The
literal,
definition of
restrictions,
CLP
then that
CLP
forcing
additional expressive
which we do not have space
always produces
the mutex's.
all
some
includes
to detail here.
a consistent set
CLP
all
wins.
literal
of conclusions, en-
also has several other attractive
well-beha\ ior properties, including about merging and about
natural belun ior of prioritization; however,
we do
not have
space here to detail these.
The courteous compiler
"adorning" predicates
tra
represents the priori-
effect
in
OLP.
tized argumentation process in
It
some
introduces
to represent the
ex-
intennediate stages
of argumentation: candidates, unrefuted candidates, skepti-
The compiler makes
cal defeat, etc..
unresolved conflict,
e.g., to raise
it
simple to detect an
an alarm about
in either
it
fonvard or backward reasoning.
From
the tractability of courteous compilation,
directly that
tion
tractable.
is
complexity
number of
Note
KIF
It
has the same worst-case time and space
OLP
as:
inferencing where the
bound v on
variables per rule has been increased to w
that
CLP
follows
it
VBD restric-
Courteous LP inferencing under the
-I-
<?xml version="l 0"?>
<clp>
<erule rulelabel="a">
<head>
<cliteral predicate=
.
"orderModi£icationNotice">
<variable name= "Order" />
< function name="daysl4 "/>
</cliteral>
</head>
<body>
<and>
<fcliteral predicate=
"preferredCustomerOf " >
<variable name= "Buyer"/
<variable name="Seller"/>
</f cliteral>
<fcliteral predicate= "purchaseOrder"
<variable name="Order"/>
<variable name = "Buyer"/
<variable name= "Seller" />
</fcliteral>
</and>
</body>
</erule>
the
2.
[rest of rules & mutex's skipped]
</clp>
overlaps syntactically and semantically with
for a broad case.
CLP
without negation-as-failure, with-
out labels (or ignoring labels), and without conflict,
tactically a restricted (essentially ,cl ausal) case
logic
(FOL)/KIF. Semantically, such
plete
when compared
to
FOL/KIF,
CLP
is
of
is
Figure
syn-
conclu-
Business Rules
XML
a
we
second aspect beyond the funda-
the rule representation concretely as
may
BRML
to
a subset
also
BRML inherits the declar-
of CLP.
ative semantics
OLP
be employing.
is
the
first
a
XML
embodiment of
CLP
of KIF, as described above,
also an
XML
I
DTD
is in
draft form; updates to
the
(1)
the
the
we do
XML
CommonRules
not have space to give
encoding.
prototype
For
full
full
details,
download package
desee:
(at
BRML
XML
approach has several advantages.
fits
into the
draft stan-
and integrating with
XML
is
translate,
WWW-world
parsing
software engineer-
easier to automatically parse, generate, edit,
XML-world
tools
links) aspects of
XML
because there are standard
forth ese tasks.
The
are also useful.
For example, a rule
some
facilitates
It
XML
developing/maintaining parsers (via standard
hyper-text
(i.e.,
set
may
via
XML
have
URL's which point to documents describing
that rule set's knowledge representation or authors or application context. Or it may have associated URL's which point
associated
to tools for processing that rule set, e.g., to execute
analyze
it,
or validate
ciated
paper,
The
As compared to the usual plain ASCII text style of embodKIF or Prolog or most programming languages,
ticularly useful for
this
this paper.
willbe posted on
iment cf
classical literal.
about
it
FIPA Agent Communication Language (ACL)
applying the negation-as-failure operator outside/in-front of a
In
(esp. "orderingleadtime" there);
forthcoming extended version of
dard.
ing.
is
contains the
communication languages, including
and
embodiment of that subset of KIF
to our knowledge, the
first XML embodiment of (any fragment oO KIF.
Figure
shows the CLP from Example 4 encoded in
BRML. Only the first rule of that Example is shown in detail, "cliteral" means "classical literal", "fcliteral"
means a rule body literal, i.e., a literal formed by optionally
tails
4.
See [14] for how
(declarative)
—
Example
larger context of agent
also expressively covers
BRML
number of examples
(2) the
tools),
our knowledge. Since
for
the authors' websites.
the
XML
embodiment of
CLP. Called Business Rules Markup Language (BRML), this
XML embodiment functions as an interlingua between heterogeneous rule representations/systems which different congive, for the first time, an
tracting agents
and
current
documents.
Next,
BRML,
http://alphaworks.ibm.com), which
and
Markup Language
Our approach includes
mental KR.W e embody
e.,
XML Data Type Definition (DTD) for BRML, explanation of
it,
XML Embodiment:
XML,i.
:
sound but incom-
in that its entailed
sions are equivalent to a (conjunctive) set of ground literals.
4.3
1
first-order-
tics
URL may
it
it,
edit
it,
(syntactically or semantically). Par-
our nearer-term purposes
is that
an asso-
point to documents describing the seman-
and algorithms for translator services or components, as
well as to translator tools and examples. Representing busi-
ness rules in
XML
has a further advantage:
it
will
comple-
ment domain-specific ontologies
XML. Many
ill
vocabularies) available
(i.e.,
are e.vpected to be developed in the ne.\t
XML
e-commerce domains. The
in
from
systems
engines
One
in
C.
els
(version
by
built
exhaustive
is
by
I),
several
ac-
These
rule
implemented
Smod-
forward-direction:
Simons,
Patrik
http //saturn hut: f i/html/st;af f /ilkka html.
The other is backward-direction: XSB, by David Warren
al,
htitp / /www cs sunysb edu/~sbprolog.
el
:
.
.
.
:
In addition,
.
we have implemented
built ourselves in Java.
sample translator
to
a sample translator to a
WFS OLP
predicate-acyclic
third,
.
.
Furthermore,
inferencing engine
we
we have implemented
a
Work
There are several other formalisms
is
to
a
BRML
is
as a free
CommonRules on the Web in July
http //alphaworks ibm.com. This proJava library that includes both the CLP and the
.
aspects of ourapp roach.
In particular,
it
includes a
courteous compiler and sample translators between
summary,we believe our approach combining CLP and
meets the whole set of requirements we gave in secany previous approach. Indeed, we believe
our approach meets every one of those requirernents
nificant degree, with
one exception: the
to a sig-
ability to express pro-
rules in a declarative
KR
for represent-
ing executable specifications of contract agreements
largely
on
their following
is
based
advantages relative to other soft-
ware specification approaches and programming languages.
First, rules are at a relatively
high level of abstraction, closer
human understandability, especially by business domain
experts who are typically non-programmers. Second, rules
to
are relatively easy to
modify dynamically and by such non-
ularity,
current work,
ther to Situated
ral
we
(i.e.,
are expressively generalizing fur-
Courteous LP's, so as
attachments as well
—
in
well-behavior
to enable
procedu-
a semantically clean
mutex's (besides implicit classical mutex's), and none has a
compiler to OLP's.
There are other, more expressively powerfiil approaches
to
and Prioritized Circumscription [19] [18]
[7] [8] that es-
handling imposes computationally intractable overhead
[6].
appears fairly straightforward to extend our
It
so as to express
in stages
KIF.
A
full first-order logic
work
direction for future
BRML,
mally compatibly with
work
In other
is
to create a
full
DTD, maxi-
that expresses full KIF.
we have extended
[21],
BRML DTD
and then
our contract rule
wards automatic configuration of auctions, including
which
ify
of a contract are
attributes
Of course,
there
yetm ore
is
promise, and achieve
work
include:
its
to
do
fiilfill
our approach's
Further issuesfo
meshing more closely with other
r
as-
pects of contracts, e.g., transactions, payments, negotiation
and communication protocols
[5] [20],
EDI, and
utility/cost-
of com-
benefit; fleshing out the relationships to a variety
mercially important rule representations/systems; representing constraints as in constraint satisfaction and Constraint
Logic Programs;
and representing delegation as
secu-
in
rity/authorization policies [17].
An
extended
as
a
version
of
paper
this
IBM
forthcoming
http //www. research
:
.
be
will
Research
avail-
Report
(at
ibra. com).
Acknowledgements
Situ-
Michael Travers(wh
ile at
IBM T.J. Watson Research
UMBC, while at IBM T.J.
and Xiaocheng Luan (of
son Research Center), contributed
attachments for condition-testing ("sensing") and action-
of the knowl-
linl<
to
ultimate goals.
nary LP's, hook beliefs to drive procedural APIs. Procedu-
edge representation: via sensor and effector
to spec-
be the subject of ne-
gotiation or bidding.
ated LP's[9] [16] [15], another expressive extension of Ordi-
("effecting'') are specified as part
to
manner
declaratively in a particular well-defined sense).
performing
(e.g., in prioriti-
zation behavior and merging). In particular, none can express
ter)
ral
mod-
consistency, unique set of conclu-
(e.g.,
and conceptual simplicity
sions), tractability,
able
programmersIn
these
nation of useful expressive power, software-engineering
fiiture
cedural attachments.
The usefulness of
work
None of
explore this dimension of heterogeneity.
representation approach with negotiation features oriented to-
XML
tion 3 better than
regard to conflict handling
direction in our current
other fonnalisms to our knowledge has as attractive a combi-
BRML
and several other rule systems/languages.
In
in
A
(see [10] [II] for a review).
alpha prototype called
totype
semantics
tex's) but different
flict
:
for prioritized LP's that
have similar syntax to Courteous LP's (except for lacking mu-
sentially can express mutex's, but in these the prioritized con-
The implementation of our approach was released
al
CLP
cyclicity/recursion restriction, e.g., to be stratified rather than
[2]
of 1999,
are also expressively generalizing
further to relax expressive restrictions such as on
prioritized default reasoning such as Prioritized Default Logic
ANSI-draft KIF (ASCII format).
Discussion and Future
5
BRML
we
work,
In current
and
(bidi-
WFS OLP
and
Niemela and
llkka
to
e.xisting
others
go
that
feasibility.
previously
link associates a predicate with an at-
predicate-acyclic.
interlingua
proof of
as
two
include
inferencing
.\ML
the
systems
rule
tual
(EDI) and other
have implemented sample translators
rectionally)
facilitates
XML.
that "talk"
Each sensor or effector
tached procedure.'
few years, including
approach also
integration with Electronic Data Interchange
e-commerce components
We
many more
such ontologies exist already, and
statements.
tation of the
'Note
CLP KR, BRML,
that "link" here
HTML hypertext link.
CenWat-
to the current
implemen-
and the associated
translators.
does not mean
in the
sense of an
XML or
Micliacl Travers' contribution
(UMBC)
bodiment. Miao Jin
was especially
XML emXML DTD.
Programs (Preliminary Report).
nary Logic
to the
contributed to the
IBM
report,
nical
Watson
T.J.
Tech-
Research
Center,
Daniel Reeves and Michael Wellrnan (ofU. Michigan) con-
http://www.research.ibni.eom/pcople/g/grosof/papers.html,
tributed to the fomiulation of the overall context and motiva-
July 1999.
tion lor
automated contract languages. Thanks
to
anonymous
[13]
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mi
Date Due
3 9080 02246 1328