Let’s look at the HebbianLink shall we?

There are three types: symmetric, asymmetric and inverse. I’ll concentrate on the symmetric HebbianLink here, but there is a paragraph about each of the others on the wiki. HebbianLinks basically indicate which concepts are important at the same time, or to put it another more OpenCog specific way, they indicate which atoms tend to appear in the Attentional focus of the system at the same time. The Truth value of the link indicates the strength of this tendency.

How these HebbianLinks are created is an interesting challenge, because we can’t just add HebbianLinks between all pairs of atoms. To intelligently do this, there are plans for a HebbianMiningAgent that will look at AtomTable activity to determine what new links should be created. However, this has yet to implemented. Currently Hebbian links have to be manually added by the programmer/user (I’ll show how I’ve done this in a later post on Hopfield network emulation using the Attention allocation mechanisms).

Once the HebbianLinks are there however, the HebbianLearningAgent keeps them updated. Each cycle the agent runs, it updates the truth values of all the HebbianLinks by adjusting them slightly to reflect the conjunction of the linked atoms when one of them is in the attentional focus.

The ImportanceSpreadingAgent takes the amount of excess importance that an atom has and spreads it along the HebbianLinks, with more importance being spread along HebbianLinks with higher TruthValues. This excess importance is defined as the amount of STI above the importance spreading threshold and this is usually greater than the attentional focus boundary to ensure that importance spreading doesn’t remove atoms from the attentional focus. This transfer of importance can then result in these destination atoms being elevated into the attentional focus, increasing their chances of being used in inference and other cognitive processes.