Cognitive Synergy between Procedural and Declarative Learning in the Control of Animated and Robotic Agents

Authors:

Year: 2011
Venue: Proceedings of AAAI-11
Links: PDF

Summary

Presents the hypothesis that “cognitive synergy” — proactive, mutually-assistive feedback between cognitive processes associated with different memory types — can serve as a foundation for advanced AGI, and details how it manifests in the procedural (MOSES) and declarative (PLN) learning algorithms of the OpenCogPrime architecture applied to controlling animated and robotic agents.

Relevance to Hyperon

A core cognitive-synergy source for the PRIMUS lineage — it operationalizes the synergy principle in OpenCogPrime's procedural/declarative learning, the conceptual ancestor of PRIMUS, and is a key articulation of the cognitive-synergy hypothesis central to Hyperon's PRIMUS architecture.

Key References

• RawData source
• PRIMUS Deep Dive