Rule Engines

Recently, there has been a proliferation of rule engines. A rule engine is by product of AI research. The basic premise is that a user is able to create a bunch of atomic units of knowledge. When the rule engine is presented with a state of the world, the rules all fire. After all the firings have settled down, the new state of the world is an outcome. A lot of problems are easier to implement using rule engines than the more conventional programming. For example, system that relies on heavy usage of knowledge with deep trees - imagine many layers deep of if/elif.

There are a couple of major contenders. For the corporate world, there is ILOG and FairIsaac. For the open source, there is Jboss Rules and Jess. Jess being the original java rule engine, and the closest to the original NASA Clips system. Clips being the system that created the rule engines. Personally, I am most familiar with Jboss Rules, ILOG and to a much lesser degree with Jess. This should not be taken as a diss on FairIsaac or any other rule engine.

Each rule engine, at its core, is based on the RETE algorithm. There are a lot of variations and enhancements, but each rule engine implements the core algorithm. The algorithm is used to find rules that need to be executed for a given world state. Imagine thousands of rules, and a good search algorithm becomes critical to a useful rule engine. The RETE algorithm acts as the control flow in a regular language.

The major blocking point to a wide adoption of rule engines is their dynamic nature and unpredictability. If you define a thousand rules, it becomes difficult to know how the rules will interact in every situation. This means testing and scenario generation is critical. This also means a much more mature infrastructure and process than most organizations have. The advantages are huge. You can explain to your user exactly how a given outcome was reached. Display the rules, modify the rules, add rules, all dynamically. You can even simplify the rule model such that your users can create their own rules.

The next blocking point is the rule language itself. The language has many requirements. For example, some people want the language to have a natural language feel. Others, want a clean interact with the existing java system, while others seek some middle ground with a scripting language. ILOG does this very well, with a natural language translation tool. Jboss rules has a more rudimentary natural language translation (DRL - DSL) but supports a wider language group.

I find Jboss Rules to be easier to get started with, but a large and mature organization should probably take a look at a vendor product for the scenario generation, and rule management infrastructure, something Jboss doesn't quite have yet. The vendors also have much more mature rule editing GUI's.