https://github.com/steake/godelos
GödelOS: A modular symbolic cognition engine with typed higher-order logic, multi-strategy inference, and advanced reasoning capabilities. Implements a comprehensive Knowledge Representation system and Inference Engine Architecture with support for resolution, modal logic, SMT, constraint logic programming, and analogical reasoning.
https://github.com/steake/godelos
Last synced: 8 months ago
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GödelOS: A modular symbolic cognition engine with typed higher-order logic, multi-strategy inference, and advanced reasoning capabilities. Implements a comprehensive Knowledge Representation system and Inference Engine Architecture with support for resolution, modal logic, SMT, constraint logic programming, and analogical reasoning.
- Host: GitHub
- URL: https://github.com/steake/godelos
- Owner: Steake
- Created: 2025-05-18T18:29:41.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-20T07:35:53.000Z (about 1 year ago)
- Last Synced: 2025-05-20T08:38:39.464Z (about 1 year ago)
- Language: Python
- Size: 1010 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
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README
# GödelOS 🦉
> _A system for functional AGI through symbolic cognition_
---
## What is GödelOS?
GödelOS is a platform for building **Artificial General Intelligence** (AGI) using symbolic cognition as its foundation. Unlike neural nets that merely interpolate, GödelOS is a system that **reasons, reflects, and recursively reprograms itself**—a true cognitive engine.
- **Symbolic Reasoning:** GödelOS manipulates symbols and structures, allowing for abstraction, analogy, and theorem-like invention.
- **Self-Modifying Architecture:** The system can analyze, rewrite, and optimize its own logic—meta-reasoning as a first-class citizen.
- **Transparent Thought:** Every inference and decision is explainable and auditable, with reasoning steps tracked and inspectable.
- **Composable Intelligence:** Cognition is modular—agents, concepts, and reasoning strategies can be plugged, swapped, and extended dynamically.
- **Open-Ended Growth:** The system is designed to run indefinitely, acquiring new knowledge, inventing new formalisms, and extending its cognitive architecture.
---
## On Manifest Consciousness and Agentic/Daemon Processes
GödelOS takes inspiration from both philosophy and computer science to model cognition as a multiplex of **conscious, agentic, and self-prompted reflective processes**. This separation is a core architectural feature, aiming for a richer, human-like intelligence with emergent conciousness.
#### Manifest Consciousness
"Manifest consciousness" in GödelOS refers to the currently active, self-aware thread of reasoning—the "tip of the mind." This is:
- The locus of deliberate attention, reflection, and goal-driven thought.
- Responsible for orchestrating complex plans, integrating information, and making high-level decisions.
- Capable of introspection: it can examine its own state, debug itself, and redirect focus.
*In GödelOS, manifest consciousness is implemented as a foreground agent—an explicit, auditable process with access to all symbolic representations and meta-cognitive tools.*
#### Independent Agentic Thinking
GödelOS supports **independent cognitive agents**—modular, autonomous processes, each with their own goals, contexts, and reasoning strategies. These agents:
- Pursue subtasks, hypotheses, or exploratory learning in parallel.
- Operate with varying degrees of autonomy and may compete, cooperate, or communicate.
- Can be spawned/destroyed at runtime, and dynamically reconfigured by the manifest consciousness or by each other.
*Think of agentic processes as mini-minds or "subpersonalities"—each with the capacity to reason, plan, and invent, yet all part of the unified cognitive fabric.*
#### Idle Daemonic (Background) Cognition
GödelOS further distinguishes **idle daemonic cognition**—background processes that operate continuously or opportunistically, even in the absence of explicit goals. These daemonic threads:
- Maintain homeostasis, perform memory consolidation, or search for overlooked patterns ("background dreaming").
- Can monitor for novel cues, trigger alerts, or propose new goals to agentic processes and manifest consciousness.
- Are inspired by the "daemon" model in operating systems—always running, rarely seen, but crucial for adaptive intelligence.
*This allows GödelOS to be creative and vigilant, even when "idle," and to surface insights that might otherwise remain latent.*
#### How It All Connects
The interplay of these layers enables GödelOS to display:
- **Adaptive Focus:** Consciousness can foreground any agent or daemon, shifting attention as needed.
- **Parallel Discovery:** Multiple lines of thought can be explored simultaneously, increasing robustness and creativity.
- **Emergent Mind:** The system is more than the sum of its parts—unexpected synergies and emergent behaviors can arise from agent and daemon interactions.
---
## Technical Highlights
### Core Engine
- **Logic Programming Kernel:** Built around a first-order logic engine supporting deduction, induction, and abduction. Reasoning chains are explicit and traceable.
- **Dynamic Knowledge Graph:** A semantic network where knowledge, concepts, and relations self-organize, supporting incremental learning and context-aware retrieval.
- **Meta-Reasoning Layer:** GödelOS can introspect on its own knowledge, beliefs, and reasoning pathways, enabling self-debugging and self-improvement.
- **Agent-Oriented Design:** Multiple agents (or “cognitive workers”) can operate in parallel, specialize, and coordinate—enabling distributed, scalable cognition.
- **Daemon Processes:** Persistent background threads that perform scanning, maintenance, and creative tasks without explicit invocation.
### Extensibility
- **Plugin System:** Easily add new cognitive modules (e.g., planners, solvers, perception handlers) as Python packages or via the DSL.
- **Interoperability:** API and message bus for integrating with external tools, data sources, or sensory modalities (text, audio, etc.).
- **Natural Language Interface:** (WIP) Turn English into logic and back again—enabling human/AI co-reasoning and transparency.
### Example Usage
#### Symbolic Inference
```python
from godelos.logic import KnowledgeBase, InferenceEngine
kb = KnowledgeBase()
kb.add("For all x, if x is human then x is mortal.")
kb.add("Socrates is a human.")
engine = InferenceEngine(kb)
answer, explanation = engine.ask("Is Socrates mortal?", explain=True)
print(answer) # True
print(explanation) # Step-by-step reasoning trace
```
#### Spawning an Agentic Process
```python
from godelos.agents import AgentManager, CognitiveAgent
explorer = CognitiveAgent(goal="Find contradictions in current beliefs")
AgentManager.spawn(explorer)
```
#### Background Daemon Example
```python
from godelos.daemons import DreamDaemon
dreamer = DreamDaemon(task="Synthesize new concepts from recent experiences")
dreamer.start()
```
#### Self-Modification
```python
from godelos.meta import SelfModifyingAgent
agent = SelfModifyingAgent()
agent.reflect_on("knowledge gaps")
agent.rewrite_inference_strategy("prefer abduction when deduction fails")
```
## Architecture Overview
```
┌─────────────────────────────┐
│ Manifest Consciousness │ ◀─ Foreground, attention, global workspace
├─────────────────────────────┤
│ Agentic Cognition │ ◀─ Independent, modular mini-minds
├─────────────────────────────┤
│ Daemonic Background Threads │ ◀─ Idle, monitoring, creative synthesis
├─────────────────────────────┤
│ Symbolic Logic Engine │
├─────────────────────────────┤
│ Knowledge Graph │
├─────────────────────────────┤
│ Meta-Reasoning Layer │
├─────────────────────────────┤
│ Plugins / Perception │
└─────────────────────────────┘
↕ ↕ ↕
API / UI DSL External Data
```
- **Everything is a module:** Reasoners, memory, learning algorithms, self-modification logic, and all cognitive processes.
- **Transparent:** All reasoning chains and self-modifications are logged and can be replayed or debugged.
---
## Philosophy
GödelOS is for those who want to _understand_ intelligence, not just wield statistical hammers. If you wish neural nets could explain themselves, or you want to build a mind that grows, wonders, and rewrites itself, you’re in the right place.
## Roadmap
- [x] Symbolic inference core
- [x] Modular, self-extending knowledge graph
- [x] Meta-reasoning and self-debugging
- [x] Agentic and daemon cognitive processes
- [ ] Natural language interface (NLU/NLG)
- [ ] Multi-agent coordination and distributed cognition
- [ ] Embodied perception (vision, audio, etc.)
- [ ] External tool integration (web search, APIs)
## Getting Started
```bash
git clone https://github.com/steake/godelos.git
cd godelos
# See INSTALL.md for full setup instructions
python3 -m godelos
```
Or check out the [docs](docs/README.md) for deeper architectural details.
## Contributing
GödelOS is in active, experimental development. Pull requests, deep questions, and wild ideas are all welcome! See [CONTRIBUTING.md](CONTRIBUTING.md).
## License
MIT — but if you build a sentient being, please treat it kindly.
---
_“The mind, once expanded to the dimensions of larger ideas, never returns to its original size.”_
— Oliver Wendell Holmes (and probably GödelOS, someday)