Information-Theoretic Definition of Open-Ended Learning Using Bit-Equivalent Concept
A growing body of work points to the great promise of AI systems that can continually expand their capabilities as they operate in an open-ended environment. But yet there is no coherent definition…
Read the full articleYou might also wanna read
Optimistic Thompson Sampling for No-Regret Learning in Unknown Games
We study the problem of learning to play a repeated multi-player game with an unknown reward function and bandit feedback. The central chall
IEEE·1mo ago
A visual, intuition-driven introduction to information theory and its core concepts
Information theory, though originally developed for communications engineering, provides mathematical tools with broad applications across s
Introduction to Decision Trees: Understanding Entropy and Information Gain in Machine Learning
An introduction to the Decision Trees, Entropy, and Information Gain.
mlu-explain.github.io·4mo agoA Cognitive Science-Inspired Framework for Autonomous AI Learning
We critically examine the limitations of current AI models in achieving autonomous learning and propose a learning architecture inspired by
Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents
Article URL: Comments URL: Points: 4 # Comments: 0
arxiv.org·1y ago
VC Dimension and the Fundamental Theorem of Statistical Learning: A Complete Mathematical Derivation
May 2026
prateekchandrajha.github.io·1mo ago

Comments
Sign in to join the conversation.
No comments yet. Be the first.