In the BREC project, we are investigating rule-based business processes for e-commerce:
both business-to-business (B2B), e.g., to integrate supply chains; and business-to-consumer (B2C).
Overall, our mission is to develop technology that is highly reusable and easy to integrate with a broad spectrum of networked applications. Towards this end, we prototype applications in tandem with developing reusable componentry. We also contribute to company-wide efforts in strategy and in common architecture, e.g., for inter-agent knowledge-level communication and inter-operability. Our reusable technology for business rules and rule-based intelligent agents is embodied as an extensible structured Java library, called CommonRules (formerly called DIPLOMAT; follow-on to RAISE and Agent Building Environment implemented in C++).
An alpha prototype of CommonRules has been released (free with trial license) on the Web, at AlphaWorks. You can see the overview of the CommonRules 1.0 release of July 30, 1999.
Specifically, we have been developing:
1. New fundamental techniques for business rules interoperability, prioritized conflict handling, and procedural attachments. These techniques include: an XML interlingua for communication; and an extended core knowledge representation, with declaratively clean semantics, that facilitates updating and execution.
2. The new techniques are embodied in a core rules technology prototype called CommonRules, formerly called "DIPLOMAT" (e.g., in many of our papers and talk slides). CommonRules is a Java library. CommonRules's starting point is:
* declarative logic programs as a core rule knowledge representation. ("Declarative" means having declarative semantics in the sense of knowledge representation theory; this is independent of details of procedural inferencing control and implementation, including of whether the direction of inferencing is forward chaining or backward chaining. Declarative semantics say what set of conclusions is sanctioned for each given set of premises. Pure Prolog, by contrast, is a particular kind of backward-inferencing logic program.)
CommonRules includes innovative functionality for:
a) courteous logic programs as a knowledge
representation, which expressively extends ordinary logic programs to enable prioritized conflict handling of a
practical and clean kind. This prioritized conflict handling.
Courteous logic programs allow the specification of
the scope of potential conflict, via pairwise mutual exclusions called
"mutex's". E.g., one might specify that discounting price by X
percent is mutually exclusive with discounting price by Y percent (whenever X
and Y are not equal). These mutual exclusions are then enforced in the sense
that the conclusion set is guaranteed to be consistent with (i.e., to respect)
all the specified mutual exclusions. Courteous logic programs also include
classical negation; a simple kind of mutual exclusion is between p and
classical-negation-of-p. Courteous logic programs further allow the
specification of partially-ordered priorities between rules. Conflict between
rules is resolved using these priorities. The prioritized conflict handling
enables modularity and locality in updating, merging, and
specifying/maintaining rule sets. Changes in rule sets can much more often be
specified simply by adding new rules, without having to modify previous rules. This
enables a more natural style of specification and communication, closer to how
humans specify and communicate rules in natural language and closer to
subclassing/inheritance in object-oriented programming.
Courteous logic programs are thus a form of
prioritized logic programs. More generally, courteous logic programs are a form
of prioritized default reasoning. Unlike previous highly expressively powerful
forms of prioritized defaults (e.g., Prioritized Circumscription or Prioritized
Default Logic), courteous logic programs are computationally tractable under
common expressive restrictions (e.g., no non-0-ary logical functions and a
bounded number of logical variables per rule).
d) an XML interlingua
(i.e., syntactic interchange format) for such translation, called Business
Rules Markup Language (BRML). The current version of BRML expresses
courteous logic programs, which overlaps with a broad subset of KIF.
* effectors that perform actions upon
drawing conclusions in rule consequents.
* sensors that perform queries during
testing of conditions in rule antecedents.
These effectors and sensors are specified by
statements that "link" (i.e., associate) them to predicates. These
effector and sensor link statements are treated as part of the knowledge
representation, similarly to rules and mutex's.
f) a sample rules engine, that
does forward-direction exhaustive inferencing for a broad case of situated
courteous/ordinary logic programs.
An alpha-version prototype of this core
technology will soon be released (free with trial license) on the Web,
on IBM's AlphaWorks site. Planned
release date for this first alpha version of CommonRules is July 30, 1999.
The rationale for the name "CommonRules" is
as follows. Our approach/prototype supports rules that are common in the
sense of a highly interoperable knowledge representation, with consensus
semantics shared by many heterogeneous rule systems/languages. The XML
interlingua in particular is a common syntactic format. The courteous
expressive extension provides some "common-sense" reasoning
capabilities, in the sense of knowledge representation theory and artificial
intelligence, because the prioritized conflict handling enables rules to be
specified in a more modular and natural style, closer to natural language and
object-oriented subclassing/inheritance.
We have further been developing a new pilot
applications for these fundamental business rules techniques in intelligent
agents and e-commerce. These applications include especially:
a) negotiations, including
procurements & auction configuration
b) catalogs & storefronts
c) security authorization &
trust management
and also other applications such as financial.
As part of all this, our group leads a major portion (including the
IBM Research portion and additional aspects) of the $29 Million EECOMS NIST match-funded ATP project, a 3-year industry consortium project
(1998-2001) in intelligent agent-based manufacturing supply chain integration,
led by IBM, also including Baan, Boeing, TRW, several universities, and some
smaller companies. Our role is in the use of rules, especially for the contents
of negotiation messages, e.g., product/service descriptions and conditions.
The Information Economies Project also grew out of the earlier Intelligent Agents
project. It investigates economies composed of intelligent agents that buy and
sell to each other, including brokering, learning, pricing, game-theory, and
large-scale market phenomena. It thus explores issues that will in future be
important for practical e-commerce agents, including those built using the
techniques in the BREC project.
(Started in 1997,
this project grew out of the earlier Intelligent Agents project (1994-97) at IBM T.J. Watson Research Center.)
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