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The system performs sequence formation steps, under attentional control, which then become concepts. These concepts try to predict other sequences based on the observation of its own sequence: For instance, concept a becomes a predictor for event b, so that after repeatedly observing ab, concept a will predict the occurrence of b after the observation of a, based on the within concept a, by Induction and Revision built predictive hypothesis a =/> b. This can be seen as some kind of Inference too. Here, derived sequences feed back to the attention buffer, while a predictive hypothesis a =/> b directly goes back to a. The sequences (with 1-ary sequences as special case), are however not terms like in OpenNARS, instead they are represented as a Sparse Distributed Representations (SDR). This allows the system to see new sequences as a special case of others with little resource effort, leading to the creation and usage of a taxonomy within the memory, almost for free.
Since events can be goals, the knowledge a =/> b can also be used backwards by the concept, to generate goal a! based on goal b! as a form of Deduction. For this purpose, a =/> b is also going back to b, which makes the green links in the diagram look special.
Input: https://github.com/patham9/ANSNA/wiki/Input
Attention buffer: A fixed-size priority queue, ordering events according to their Attention Value.
Concepts: A fixed-size priority queue, ordering concepts, named by SDR's according to their Attention Value.
Overall working cycle example: https://github.com/patham9/ANSNA/wiki/Working-cycle
Action: A fixed procedure triggered by the derivation of a goal of high desire value that got processed in its concept.
Inference:
Revision:
{Event a., Event a.} |- Event a.
{Event a!, Event a!} |- Event a!
{Implication <a =/> b>., Implication <a =/> b>.} |- Implication <a =/> b>.
Deduction:
{Event a., Implicatiom <a =/> b>.} |- Event b.
{Event b!, Implication <a =/> b>.} |- Event a!
SDRMatch (https://github.com/patham9/ANSNA/wiki/SDRInheritance-for-matching,-and-its-truth-value)
Induction:
{Event a., Event b.} |- Implication <a =/> b>.
Abduction:
{Event b., Implication <a =/> b>.} |- Event a.
{Event a!, Implication <a =/> b>.} |- Event b!
Intersection:
{Event a., Event b.} |- Event (&/,a,b).