Building Better Minds

How to Use This Source

Building Better Minds: Artificial General Intelligence via the Cog' Architecture
Ben Goertzel with Cassio Pennachin, Nil Geisweiller & the OpenCog Team. August 2012 (preliminary draft). 48 chapters across 2 parts + appendices, stored in 52 chunks.

This is the historical foundation for the Hyperon/PRIMUS architecture. It describes CogPrime (the predecessor to PRIMUS) and the OpenCog system that preceded Hyperon. Most wiki cards covering PLN, MOSES, ECAN, pattern mining, attention allocation, and the cognitive synergy principle trace their conceptual lineage to this book.

Reading strategy: This book is not a direct description of the current Hyperon system — it describes the CogPrime/OpenCog era. Use it for: (1) understanding why current components exist, (2) the philosophical framework (patternism) underpinning the project, (3) detailed technical specifications of PLN, MOSES, ECAN that remain largely valid, and (4) the ethics and self-modification framework that evolved into the 2025 whitepaper's §8. For the current system state, use the Whitepaper 2025 Map instead.

Thematic Map

Theme	Chapters	Chunks	Cards Grounded
Philosophy & Intelligence Theory Patternism, general intelligence definitions, mind-world correspondence, cognitive synergy principle	1–3, 8–10	1, 3–5, 10–11	PRIMUS Full (cognitive synergy lineage)
Cognitive Architectures Survey SOAR, ACT-R, NARS, Cyc, DeSTIN, LIDA, Psi, MicroPsi, Global Workspace	4–5	6–8	OpenCog Legacy history
CogPrime Design Overview Architecture, memory types, goal-oriented dynamics, analysis/synthesis	6–7	8–9	OpenCog Legacy history, PRIMUS Full
Cognitive Development & Ethics Piaget stages, Friendly AI, Coherent Extrapolated Volition, AGI societies, eight ways to bias toward friendliness	11–12	12–15	Self-Modification and Safety
Knowledge Representation Weighted labeled hypergraphs, glocal memory, AtomSpace architecture, atom types, procedural knowledge (Combo language)	13–15, 19–21	16–17, 20–23	AtomSpace Full, Knowledge Substrates
AGI Preschool & Roadmap Virtual preschool design, curriculum, assessment, self-modification via supercompilation and theorem-proving	16–18	18–19	Self-Modification and Safety Full (Ch 18 lineage), Game Worlds
Cognitive Cycle Emotion/motivation (Psi model), ECAN (STI/LTI, Hebbian links, information geometry), economic goal selection	22–25	24–26	ECAN Full, MetaMo Full (Psi→MetaMo lineage)
Perception & Action Perceptual-motor hierarchies, DeSTIN deep learning, symbolic/subsymbolic bridge	26–29	27–29	Robotics
Procedure Learning (MOSES) IRC learning, hillclimbing, MOSES/EDA, hierarchical program learning, fitness estimation	30–33	30–32	MOSES Full, Reasoning and Search
Declarative Learning (PLN) PLN truth values and rules, spatiotemporal inference, inference control, pattern mining (Fishgram), concept blending	34–38	33–35	PLN Full, Semantic Parsing Full
Integrative Learning Dimensional embedding, episodic memory, map formation, procedure encapsulation	39–42	37, 44	PRIMUS Full (integration model)
Natural Language Psynese (inter-mind communication), Link Grammar, RelEx, NL comprehension/generation, embodied language	43–47	38–42	Semantic Parsing Full, Knowledge Substrates (Link Grammar)
Summary & Synthesis Argument for Cog' approach, synergies between components	48	2, 43	PRIMUS Full
Appendices A: Glossary. B: Category theory (functors for memory conversion). C: Hyperset model of consciousness. D: GOLEM self-modification. F: Neural inheritance & term logic. H: Propositions about Cog'/PLN	App A–H	45–51	Self-Modification and Safety Full (App D: GOLEM)
References	—	52	—

CogPrime → Hyperon Correspondence

The most valuable use of BBM for wiki enrichment is tracing how CogPrime components evolved into current Hyperon/PRIMUS ones:

BBM / CogPrime	BBM Chapters	Current Hyperon/PRIMUS
AtomSpace (weighted labeled hypergraph)	13–14, 19–20	AtomSpace (retained), MORK (new substrate)
PLN (truth values, inference rules)	34–36	PLN on quantale-annotated factor graphs
MOSES (EDA + evolutionary programming)	30–33	MOSES/GEO-EVO with geodesic search
ECAN (STI/LTI, Hebbian links)	23	ECAN with fluid-dynamic extension
Pattern mining (Fishgram)	37	Stream-based pattern mining with I-surprisingness
Concept blending	38	Concept blending (retained, now TransWeave-compatible)
Psi motivational model	22	MetaMo (pseudo-bimonad replacement)
Cognitive synergy	8	PRIMUS cooperation model / TransWeave formalization
Self-modification	18, App D	Five-stage pipeline with supermartingale potentials
Link Grammar + RelEx	44–45	Semantic Parsing (retained + Symbolic Heads)
DeSTIN perception	26–29	QuantiMORK (inside integration)
OpenCog framework	19	Hyperon (MeTTa + Space API + DAS)

Best Source For...

• Why cognitive synergy matters: Ch 8 (chunks 10) — the foundational argument for multi-paradigm integration
• Patternist philosophy: Ch 3 (chunks 4–5) — the philosophical framework underlying the entire project
• Original PLN specification: Ch 34–36 (chunks 33–34) — truth value formulas, inference rules, control strategies
• Original MOSES specification: Ch 33 (chunk 32) — EDA, deme structure, knob-based representation
• Original ECAN specification: Ch 23 (chunks 24–25) — STI/LTI semantics, update equations, information geometry
• Psi→MetaMo lineage: Ch 22 (chunk ~24) — emotion/motivation model that MetaMo supersedes
• AGI ethics foundations: Ch 12 (chunks 13–15) — Friendly AI, CEV/CAV, ethical development stages
• Self-modification history: Ch 18 + App D (chunk 19, chunks 49) — GOLEM, supercompilation, precursors to the 2025 pipeline
• OpenCog architecture: Ch 19 (chunks 20–21) — AtomSpace, MindAgents, cognitive cycle
• Link Grammar / NLP pipeline: Ch 44 (chunks 39–40) — parsing, RelEx, Frame2Atom
• DeSTIN perception: Ch 28 (chunk 28) — the deep learning perception system that preceded QuantiMORK
• Preschool / embodied AGI: Ch 16 (chunk 18) — the virtual preschool concept behind current game-world pilots

Enrichment Targets

BBM content that could deepen existing wiki cards in a future enrichment pass:

BBM Theme	Target Card	Priority	What to Add
Ch 8: Cognitive Synergy	PRIMUS Full	Medium	The original cognitive synergy argument — specific synergy pairs (PLN↔MOSES, ECAN↔PLN) that motivated the architecture
Ch 22: Psi Model	MetaMo Full	Medium	Detailed OpenPsi→MetaMo transition story with specific limitations of the Psi model that MetaMo addresses
Ch 12: Ethics	Self-Modification and Safety Full	Low	Historical ethics framework (CEV/CAV, eight friendliness biases) — already cited but not detailed
Ch 38: Concept Blending	No dedicated card	Low	Blending theory criteria (topology, web, unpacking, metonymic tightening) — matches whitepaper §6.5 gap
App B: Category Theory	AtomSpace Full	Low	Functor-based model of memory type conversions — historical precursor to the Space API abstraction