DreamLog: Neural-Symbolic Integration through Compression-Based Learning and Wake-Sleep Cycles
We present DreamLog, a neural-symbolic system that integrates logic programming with large language models (LLMs) through a biologically-inspired architecture featuring wake-sleep cycles, compression-based learning, and recursive knowledge generation. DreamLog addresses the fundamental challenge of …
Discussion & Related
DreamLog: Logic Programming That Dreams to Improve Itself
A logic programming system that alternates between wake and sleep phases, using LLMs for knowledge generation during wake and compression-based learning during sleep.
October 8, 2025 · 3 min read
The Policy: Q-Learning vs Policy Learning
SIGMA uses Q-learning rather than direct policy learning. This architectural choice makes it both transparent and terrifying. You can read its value function, but what you read is chilling.
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