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sunghunkwag/README.md

Independent AI Researcher

I design AI architectures through hypothesis-driven research. My repositories constitute an experimental portfolio testing foundational assumptions about scalable intelligence systems using AI-augmented conceptual modeling methodologies.

Contact: sunghunkwag@gmail.com

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  1. DHC-SSM-Enhanced DHC-SSM-Enhanced Public

    DHC-SSM v3.0: Production-ready Deterministic Hierarchical Causal State Space Model with O(n) complexity

    Python 1

  2. MetaRL-Agent-Framework MetaRL-Agent-Framework Public

    MetaRL Agent Framework: Modular meta-reinforcement learning system with extensible agent coordination and adaptation.

    Python 1

  3. SSM-MetaRL-TestCompute SSM-MetaRL-TestCompute Public

    Unified meta-reinforcement learning benchmark for fast adaptation with State Space Models (SSM), test-time improvement, and modular policy orchestration. Includes automated training, evaluation, ad…

    Python

  4. heterogeneous-agent-swarm heterogeneous-agent-swarm Public

    Research prototype for experimenting with heterogeneous multi-agent swarms under explicit cost, budget, and control constraints. Focused on cost-aware coordination, meta-level control, and structur…

    Python