vST for Robotics and Control Policies#

References#

This appendix lists references relevant to robotics, control policies, reinforcement learning, high‑dimensional latent‑space analysis, scaling laws, dynamical systems, and validation frameworks. Citations are grouped by category for clarity and presented in a substrate‑agnostic, model‑independent format consistent with the RSM and vST canon.

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).