Procedure Encapsulation and Expansion
One of the most important special cases of map encapsulation is procedure encapsulation. This refers to the process of taking a schema/predicate map and embodying it in a single ProcedureNode. This may be done by mining on the Procedure Activity Table, described in Activity Tables, using either:
- a special variant of itemset mining that seeks for procedures whose outputs serve as inputs for other procedures.
- Evolutionary optimization with a fitness function that restricts attention to sets of procedures that form a digraph, where the procedures lie at the vertices and an arrow from vertex A to vertex B indicates that the outputs of A become the inputs of B.
The reverse of this process, procedure expansion, is also interesting, though algorithmically easier — here one takes a compound ProcedureNode and expands its internals into a collection of appropriately interlinked ProcedureNodes. The challenge here is to figure out where to split a complex Combo tree into subtrees. But if the Combo tree has a hierarchical structure then this is very simple; the hierarchical subunits may simply be split into separate ProcedureNodes.
These two processes may be used in sequence to interesting effect: expanding an important compound ProcedureNode so it can be modified via reinforcement learning, then encapsulating its modified version for efficient execution, then perhaps expanding this modified version later on.
To an extent, the existence of these two different representations of procedures is an artifact of OCP's particular software design (and ultimately, a reflection of certain properties of the von Neumann computing architecture). But it also represents a more fundamental dichotomy, between:
- Procedures represented in a way that is open to interaction with other mental processes during the execution process.
- Procedures represented in a way that is encapsulated and mechanical, with no room for interference from other aspects of the mind during execution.
Conceptually, we believe that this is a very useful distinction for a mind to make. In nearly any reasonable cognitive architecture, it's going to be more efficient to execute a procedure if that procedure is treated as a world unto itself, so it can simply be executed without worrying about interactions. This is a strong motivation for an artificial cognitive system to have a dual (at least) representation of procedures.
Procedure Encapsulation in More Detail
For a visual depiction of the procedure encapsulation process, see the attachment.
A procedure map is a temporal motif: it is a set of Atoms (ProcedureNodes), which are habitually executed in a particular temporal order, and which implicitly pass arguments amongst each other. For instance, if procedure A acts to create node X, and procedure B then takes node X as input, then we may say that A has implicitly passed an argument to B.
The encapsulation process can recognize some very subtle patterns, but a fair fraction of its activity can be understood in terms of some simple heuristics.
For instance, map encapsulation process will create a node h = B f g = f composed with g when there are many examples in the system of:
ExecutionLink g x y ExecutionLink f y z
The procedure encapsulation process will also recognize larger repeated subgraphs, and their patterns of execution over time. But some of its recognition of larger subgraphs may be done incrementally, by repeated recognition of simple patterns like the ones just described.
Procedure Encapsulation in the Human Brain
Finally, we will briefly discuss some conceptual issues regarding the relation between OCP procedure encapsulation and the human brain. Current knowledge of the human brain is weak in this regard, but we won't be surprised if, in time, it is revealed that the brain stores procedures in several different ways, that one distinction between these different ways has to do with degree of openness to interactions, and that the less open ways lead to faster execution.
Generally speaking, there is good evidence for a neural distinction between procedural, episodic and declarative memory. But knowledge about distinctions between different kinds of procedural memory is scantier. It is known that procedural knowledge can be "routinized" — so that, e.g., once you get good at serving a tennis ball or solving a quadratic equation, your brain handles the process in a different way than before when you were learning. And it seems plausible that routinized knowledge, as represented in the brain, has fewer connections back to the rest of the brain than the pre-routinized knowledge. But there will be much firmer knowledge about such things in 5 to 10 years time as brain scanning technology advances.
There is more neuroscience knowledge about motor procedures than cognitive procedures (see e.g. Reza and Wise, 2005). Much of motor procedural memory resides in the pre-motor area of the cortex. The motor plans stored here are not static entities and are easily modified through feedback, and through interaction with other brain regions. Generally, a motor plan will be stored in a distributed way across a significant percentage of the premotor cortex; and a complex or multipart actions will tend to involve numerous sub-plans, executed in both parallel and in serial. Often what we think of as separate/distinct motor-plans may in fact be just slightly different combinations of subplans (a phenomenon also occurring with schema maps in OCP).
In the case of motor plans, a great deal of the routinization process has to do with learning the timing necessary for correct coordination between muscles and motor subplans. This involves integration of several brain regions — for instance, timing is handled by the cerebellum to a degree, and some motor-execution decisions are regulated by the basal ganglia.
One can think of many motor plans as involving abstract and concrete sub-plans. The abstract sub-plans are more likely to involve integration with those parts of the cortex dealing with conceptual thought. The concrete sub-plans have highly optimized timings, based on close integration with cerebellum, basal ganglia and so forth — but are not closely integrated with the conceptualization-focused parts of the brain. So, a rough OCP model of human motor procedures might involve schema maps coordinating the abstract aspects of motor procedures, triggering activity of complex SchemaNodes containing precisely optimized procedures that interact carefully with external actuators.