Wongi::Engine

This library contains a rule engine written in Ruby. It's based on the Rete algorithm and uses a DSL to express rules in a readable way.

Installation

Add this line to your application's Gemfile:

gem 'wongi-engine'

And then execute:

$ bundle

Or install it yourself as:

$ gem install wongi-engine

Tutorial

To begin, say

engine = Wongi::Engine.create

Now let's add some facts to the system.

Facts

All knowledge in Wongi::Engine is represented by triples of { subject, predicate, object }. Predicates usually stand for subjects' properties, and objects for values of those properties. More complex types can always be decomposed into such triples.

Triples can contain any Ruby object that defines the == comparison in a meaningful way, but some symbols have special meaning, as we will see.

Try this:

engine << [ "Alice", "friend", "Bob" ]
engine << [ "Alice", "age", 35 ]

What can we do with this information?

Simple iteration

Suppose we want to list all we know about Alice. You could, for instance, do:

engine.each "Alice", :_, :_ do |item|
	puts "Alice's #{item.predicate} is #{item.object}"
end

each takes three arguments for every field of a triple and tries to match the resulting template against the known facts. :_ is the special value that matches anything. This kind of pattern matching plays a large role in Wongi::Engine; more on that later.

In a similar way, you can use select to get an array of matching facts and find to get the first matching one. Both methods take three arguments.

Simple rules

It's not very interesting to use the engine like that, though. Rule engines are supposed to be declarative. Let's try this:

friends = engine.rule "friends" do
	forall {
		has :PersonA, "friend", :PersonB
	}
end

Here's your first taste of the engine's DSL. A rule, generally speaking, consists of a number of conditions the dataset needs to meet; those are defined in the forall section (also spelled for_all, if you prefer that). has (or fact) specifies that there needs to be a fact that matches the given pattern; in this case, one with the predicate "friends".

When a pattern contains a symbol that starts with an uppercase letter, it introduces a variable which will be bound to an actual triple field. Their values can be retrieved from the result set:

friends.tokens.each do |token|
	puts "%s and %s are friends" % [ token[ :PersonA ], token[ :PersonB ] ]
end

A token represents all facts that passed the rule's conditions. If you think of the dataset as of a long SQL table being joined with itself, then a token is like a row in the resulting table.

If you don't care about a specific field's value, you can use the all-matcher :_ in its place so as not to introduce unnecessary variables.

Once a variable is bound, it can be used to match further facts within a rule. Let's add another friendship:

engine << [ "Bob", "friend", "Claire" ]

and another rule:

remote = engine.rule "remote friends" do
	forall {
		has :PersonA, "friend", :PersonB
		has :PersonB, "friend", :PersonC
	}
end

remote.tokens.each do |token|
	puts "%s and %s are friends through %s" % [ token[ :PersonA ], token[ :PersonC ], token[ :PersonB ] ]
end

(engine.rule returns the created production node - an object that accumulates the rule's result set. You don't have to carry it around if you don't want to - it is always possible to retrieve it later as engine.productions["remote friends"].)

Stored queries

Taking the SQL metaphor further, you can use the engine to do fancy searches:

q = engine.query "friends" do
	search_on :Name
	forall {
		has :Name, "friend", :Friend
	}
end

engine.execute "friends", { Name: "Alice" }
q.tokens.each do |token|
	... # you know the drill
end

Not that this is a particularly fancy search, but you get the idea.

Queries work the same way as normal rules, but they come with some variables already bound by the time matching starts.

You can also retrieve the query's production node from engine.results["friends"] (they are intentionally kept separate from regular productions).

Taking an action

There's more to rules than passive accumulation:

engine.rule "self-printer" do
	forall {
		has :PersonA, "friend", :PersonB
	}
	make {
		action { |token|
			puts "%s and %s are friends" % [ token[ :PersonA ], token[ :PersonB ] ]
		}
	}
end

The make section (also spelled do!, if you find it more agreeable English, because do is a keyword in Ruby) lists everything that happens when a rule's conditions are fully matched (we say the production node is activated). Wongi::Engine provides only a small amount of build-in actions, but you can define define your own ones, and the simplest one is just action with a block.

More facts!

Note how our facts define relations that always go from subject to object - they form a directed graph. In a perfect world, friendships go both ways, but to specify this in out model, we need to have two facts for each couple. Instead of duplicating everything by hand, let's automate that:

engine.rule "symmetric predicate" do
	forall {
		has :Predicate, "symmetric", true
		has :X, :Predicate, :Y
	}
	make {
		gen :Y, :Predicate, :X
	}
end

engine << ["friend", "symmetric", true]

If you still have the "self-printer" rule installed, you will see some new friendships pop up immediately!

The built-in gen action creates new facts, taking either fixed values or variables as arguments. (It will complain if use provide a variable that isn't bound by the time it's activated.) Here, it takes all relations we've defined to be symmetric, finds all couples in those sorts of relations and turns them around.

Matchers

It wouldn't be very useful if has were the only sort of condition that could be used. Here are some more:

neg subject, predicate, object

Passes if the specified template does not match anything in the dataset. Alias: missing.

maybe subject, predicate, object

Passes whether or not the template matches anything. It's only useful if it introduces a new variable. Alias: optional.

none { ... }

The none block contains other matchers and passes if that entire subchain returns an empty set. In other words, it corresponds to an expression not ( a and b and ... ).

any { option { ... } ... }

The any block contains several option blocks, each of them containing other matchers. It passes if any of the option subchains matches. It's a shame that disjunction has to be so much more verbose than conjunction, but life is cruel.

same x, y

Passes if the arguments are equal. Alias: eq, equal.

diff x, y

Passes if the arguments are not equal. Alias: ne.

Timeline

Wongi::Engine has a limited concept of timed facts: time is discrete and only extends into the past. Matchers that accept a triple specification (has, neg and maybe) can also accept a fourth parameter, an integer <= 0, which will make them look at a past state of the system. "0" means the current state and is the default value, "-1" means the one just before the current, and so on.

To create past states, say:

engine.snapshot!

This will shift all facts one step into the past. The new current state will be a copy of the last one. You can only insert new facts into the current state, "retroactive" facts are not allowed.

Time-aware matchers

The following matchers are nothing but syntactic sugar for a combination of primitives.

asserted subject, predicate, object

Short for:

neg subject, predicate, object, -1
has subject, predicate, object, 0

That is, it passes if the fact was missing in the previous state but exists in the current one. Alias: added.

retracted subject, predicate, object

Short for:

has subject, predicate, object, -1
neg subject, predicate, object, 0

The reverse of asserted. Alias: removed.

kept subject, predicate, object

Short for:

has subject, predicate, object, -1
has subject, predicate, object, 0

Alias: still_has.

kept_missing subject, predicate, object

Short for:

neg subject, predicate, object, -1
neg subject, predicate, object, 0

Alias: still_missing.

Other built-in actions

collect variable, collector_name

If you use this action, engine.collection( collector_name ) will provide a uniq'ed array of all values variable has been bound to. It's a bit shorter than iterating over the tokens by hand.

error message, error { |hash_of_variable_assignments| ... }

Useful when you want to detect contradictory facts. engine.errors will give an array of all error messages produced when this action is activated. If you use the block form, the block needs to return a message.

trace options

The debugging action that will print a message every time it's activated. Possible options are:

• values (boolean = false): whether to print variable assignments as well
• io (IO = $stdout): which IO object to use
• generation (boolean = false): whether this rule's gen action should print messages too. trace must come before any gen actions in this case.
• tracer, tracer_class: a custom tracer that must respond to trace and accept a hash argument. Hash contents will vary depending on the action being traced.

Custom actions

We've seen one way to specify custom actions: using action with a block. Another way to use it is to say:

action class, ... do
	...
end

Any additional arguments or blocks will be given to initialize, and the class must define an execute method taking a token. Passing any object with an execute method also works.

If your action class inherits from Wongi::Engine::Action, you'll have the following (more or less useful) attributes:

• rete: the engine instance
• rule: the rule object that is using this action
• name: the extension clause used to define this action (read more under DSL extensions)
• production: the production node

If you can't or don't want to inherit, you can define the accessors yourself. Having just the ones you need is fine.

Organising rules

Using engine.rule and engine.query is fine if you want to experiment, but to make rules and queries more manageable, you will probably want to keep them separate from the engine instance. One way to do that is to just say:

my_rule = rule "name" do
	...
end

engine << my_rule

For even more convenience, why not group rules together:

my_ruleset = ruleset {
	rule "rule 1" do
		...
	end
	rule "rule 2" do
		...
	end
}

engine << my_ruleset

Again, you don't need to hold on to object references if you don't want to:

ruleset "my set" do
	...
end

engine << Wongi::Engine::Ruleset[ "my set" ]

DSL extensions

This is a more advanced method of customising. In general, DSL extensions have the form:

dsl {
	section [ :forall | :make ]
	clause :my_action
	[ action | accept | body ] ...
}

which is then used in a rule like this:

make {
	my_action ...
}

DSL extensions are globally visible to all engine instances.

Let's have a look at the three ways to define a clause's implementation.

body { |...| ... }

This simply allows you to group several other actions or matchers. It is perhaps the only way you have to extend the forall section, as any non-trivial matchers will require special support from the engine itself.

action class, action do |token| ... end

This works almost exactly like using the action action directly in a rule, but gives it a more meaningful alias. Arguments to initialize, however, are taken from the action's invocation in make, not the definition.

A useful pattern is having specialised named collectors, defined like this:

dsl {
	section :make
	clause :my_collection
	action Wongi::Engine::SimpleCollector.collector
}

installed like this:

rule('collecting') {
	...
	make {
		my_collection :X
	}
}

and accessed like this:

collection = engine.collection :my_collection

accept class

Most library users probably won't need this, but it's here for completion. Acceptors represent an intermediate state. They allow you to have some shared data that you customize for a given engine instance. The class needs to respond to import_into( engine_instance ) and return something usable as an action, or to be usable as an action itself.

The class also gets arguments to initialize from the action's invocation.

Acknowledgements

The Rete implementation in this library largely follows the outline presented in [Doorenbos, 1995].

Changelog

0.0.1

• initial repackaged release

Contributing

1. Fork it
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Added some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create new Pull Request