Progressive
Capabilities accumulate through explicit learning, experience, and distinct stages of development.
High-level intelligent systems
A legible architecture for intelligence.
A language-centered theory of how intelligent systems represent knowledge, reason, learn, form intentions, and act.
FIG. 01SYSTEM / REALM
INFORMATION↓
INPUT INTERFACEinterpret
ATTENTION REALM
LLANGUAGE
IINFERENCE
TENTITIES
↺ LEARNING / CHANGE
intendACTION INTERFACE
↓ACTION
An intelligent system receives information, changes through inference and learning, and acts to pursue an intention.
01 / DEFINITION
An intelligent system receives input through its senses, reasons from experience, changes sustainably through learning, and acts in an attempt to realize an intention.
“High-level” is a point of view, not a class of machine.
RAISE describes intelligence through structures that people can examine and discuss. It is designed to work alongside low-level methods such as machine learning—not to displace them.
Data-efficient
Structured knowledge and inference allow a system to reuse what it already knows.
Transparent
Knowledge, reasoning paths, intentions, and changes can be represented and inspected.
02 / ARCHITECTURE
From language
to action.
RAISE starts with language-readable representations of knowledge, then follows the transformations that turn information into inference, learning, intention, and observable action.
Language
Natural expression becomes structured true-value statements.
Inference
Rules and inference chains drive changes in cognitive state.
Entities
Entities, concepts, and knowledge trees organize recognition.
Realms
Truths receive boundaries of context, validity, and time.
Learning
New truths and contradiction resolution produce lasting change.
Action
Utility, goals, and intention resolve into plans and behavior.
TWO COMPLEMENTARY SCALES
Structure above.
Mechanism below.
Knowledge, reasoning, learning, intention, and system behavior.
↕HYBRID SYSTEM
Signals, perception, statistical learning, and computational mechanisms.
03 / THE BOOK
A guided route
through the theory.
The book moves from the foundations of a theoretically complete system to the constraints, decisions, and learning processes of real intelligent systems.
PART IFoundations of complete systems
00
Development of the Theory
From early language research to the high-level framework.
↗01The L System
Language, notation, and true-value statements.
↗02The I System
Rules, inference matrices, and chains of reasoning.
↗03The T System & LIT
Entities, concept intermediaries, and knowledge trees.
↗04Realms
The boundaries within which truths retain their validity.
↗05Systems
Interfaces, observation, action, function, and isomorphism.
↗PART IIIncomplete systems
06
Incomplete Systems
Attention, finite memory, and bounded inference.
↗07Action
Utility, goals, intentions, plans, dialogue, and strategy.
↗08Complex Reasoning
Reserved for a future edition of the theory.
IN DEVELOPMENT↗09Learning
New truths, contradiction resolution, and stability.
↗10Error
Relative errors, absolute errors, and non-optimal states.
↗11Implementation
Base-derived, embodied, and sensory-derived routes.
↗12Further Questions
Emotion, beliefs, safety, and superintelligence.
↗04 / READ
The complete
first preprint.
The Chinese-language first edition presents the boundaries, tools, evolution, implementation routes, and open questions of High-Level Intelligent Systems Theory.
- Length
- 221 pages
- Format
- PDF · 3.1 MB
- Status
- First edition · Preprint
05 / WATCH
Theory, one
chapter at a time.
A companion video series will follow the book chapter by chapter—building the vocabulary first, then connecting language, inference, learning, and action into one system.
Visit the channelTemporary channel — the destination can be switched when the dedicated RAISE channel is ready.
01
The L System
SERIES / PLANNED↗02The I System
SERIES / PLANNED↗03The T System & LIT
SERIES / PLANNED↗04Realms
SERIES / PLANNED↗05Systems
SERIES / PLANNED↗06Incomplete Systems
SERIES / PLANNED↗07Action
SERIES / PLANNED↗08Complex Reasoning
BOOK CHAPTER IN DEVELOPMENT↗09Learning
SERIES / PLANNED↗10Error
SERIES / PLANNED↗11Implementation
SERIES / PLANNED↗12Further Questions
SERIES / PLANNED↗06 / EVOLUTION
Eight years
of development.
The framework developed non-linearly, replacing earlier tools as more coherent descriptions of intelligent behavior emerged.
LIT architecture
Language, entities, and inference become the starting point.
Truth & realms
True-value statements, inference matrices, and validity boundaries.
Systems that act
Attention, intention, action, and a formal definition of systems.
Isomorphism
Function, explainability, transitions, and learning through contradiction.
Stability
High-level collaboration with language models and new realm notation.
Incomplete systems
Inference distance, fallback stacks, and the first preprint.
07 / AN OPEN FRAMEWORK
Built to be
questioned.
RAISE Theory is at an early stage. Researchers, engineers, philosophers, and readers are invited to test its assumptions, criticize its tools, and extend the framework.
rkc@raise-theory.com Comments, corrections, and collaboration