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vST for Robotics and Control Policies#

References#


1. Robotics and Control Systems#

  • Siciliano, B., & Khatib, O.
    Springer Handbook of Robotics.
    Springer (2016).

  • Spong, M. W., Hutchinson, S., & Vidyasagar, M.
    Robot Modeling and Control.
    Wiley (2006).

  • LaValle, S. M.
    Planning Algorithms.
    Cambridge University Press (2006).


2. Reinforcement Learning and Policy Optimization#

  • Sutton, R. S., & Barto, A. G.
    Reinforcement Learning: An Introduction.
    MIT Press (2018).

  • Schulman, J., Wolski, F., Dhariwal, P., et al.
    Proximal Policy Optimization Algorithms.
    arXiv:1707.06347 (2017).

  • Haarnoja, T., Zhou, A., Abbeel, P., & Levine, S.
    Soft Actor‑Critic: Off‑Policy Maximum Entropy Deep RL.
    ICML (2018).


3. High‑Dimensional Latent‑Space Modeling#

  • Kingma, D. P., & Welling, M.
    Auto‑Encoding Variational Bayes.
    arXiv:1312.6114 (2013).

  • Vaswani, A., Shazeer, N., Parmar, N., et al.
    Attention Is All You Need.
    NeurIPS (2017).

  • Chung, J., Gulcehre, C., Cho, K., & Bengio, Y.
    Gated Recurrent Neural Networks.
    arXiv:1412.3555 (2014).


4. Scaling Laws and Multi‑Modal Policies#

  • Kaplan, J., McCandlish, S., Henighan, T., et al.
    Scaling Laws for Neural Language Models.
    arXiv:2001.08361 (2020).

  • Radosavovic, I., Xiao, T., James, S., et al.
    Real‑World Robot Learning with Masked Visual Pre‑Training.
    arXiv:2306.05425 (2023).

  • Zeng, A., Florence, P., Tompson, J., et al.
    Transporter Networks: Rearranging the Visual World for Robotic Manipulation.
    CoRL (2020).


5. Dynamical Systems and Regime Behavior#

  • Strogatz, S.
    Nonlinear Dynamics and Chaos.
    Westview Press (2014).

  • Khalil, H. K.
    Nonlinear Systems.
    Prentice Hall (2002).

  • Guckenheimer, J., & Holmes, P.
    Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields.
    Springer (1983).


6. Validation, Verification, and Drift Detection#

  • Amodei, D., Olah, C., Steinhardt, J., et al.
    Concrete Problems in AI Safety.
    arXiv:1606.06565 (2016).

  • Breck, E., Cai, S., Nielsen, E., et al.
    The ML Test Score: A Rubric for ML Production Readiness.
    Google Research (2017).

  • Oberkampf, W. L., & Roy, C. J.
    Verification and Validation in Scientific Computing.
    Cambridge University Press (2010).


7. Substrate‑Level and Triadic‑Frameworks Canon#

  • Loswin, N.
    Resonance Substrate Model (RSM): Structural Foundations for High‑Dimensional Inference.
    TriadicFrameworks (2025).

  • Loswin, N.
    Triadic Dimensional Cores: A 3D–9D Substrate for Structural and Inference‑Level Alignment.
    TriadicFrameworks (2025).

  • Loswin, N.
    Validation‑Space‑Time (vST): A Substrate‑Level Framework for Reproducibility and Drift Detection.
    TriadicFrameworks (2025).

  • Loswin, N.
    Dimensional Substrate Structures: Scaling Laws and High‑Dimensional Regimes.
    TriadicFrameworks (2026).

  • Loswin, N.
    vST for Robotics and Control Policies.
    TriadicFrameworks (2026).