VSAVM

Vector Symbolic Architecture (VSA)

This wiki entry defines a term used across VSAVM and explains why it matters in the architecture.

The diagram has a transparent background and highlights the operational meaning of the term inside VSAVM.

Related wiki pages: VM, event stream, VSA, bounded closure, consistency contract.

Definition

Vector Symbolic Architecture represents symbols as high-dimensional vectors and supports operations such as binding and bundling. It functions as an associative index for fast retrieval and clustering.

Role in VSAVM

VSA reduces combinatorial search by shortlisting schemas and macro programs similar to a given span. It guides what the system explores under budget without deciding truth.

Mechanics and implications

VSAVM treats VSA output as proposals. Candidates are executed in the VM and checked under bounded closure. This separation preserves correctness: similarity accelerates search, but execution determines acceptability.

Further reading

Hyperdimensional computing and VSA surveys provide background on why high-dimensional representations support robust associative behavior. In VSAVM, these methods are used as search accelerators rather than as semantic authorities.

vsa diagram
VSA accelerates retrieval; the VM validates candidates under the consistency contract.

References

Vector symbolic architecture (Wikipedia) Hyperdimensional computing (Wikipedia) Nearest neighbor search (Wikipedia)