Axiocortex Research
Hierarchical World Models, Sample-Efficient Learning, and Brain-Inspired AI
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About This Research
This hub tracks research on HICA (Hierarchical Intrinsic Curiosity Agent) — a brain-inspired approach to building sample-efficient AI agents. The core idea: combine hierarchical world models (like Dreamer), complementary learning systems (hippocampus + neocortex), and predictive maps (successor representation) to create agents that learn fast, generalize well, and plan hierarchically.
World Models Dreamer CLS Theory Successor Representation Hierarchical RL Sample Efficiency Predictive Coding