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fix(phase-09/02): add Bertsekas and Tsitsiklis neuro-DP as bridge to deep RL lessons

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Rohit Ghumare
2026-04-23 00:45:43 +01:00
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phases/09-reinforcement-learning/02-dynamic-programming/docs/en.md
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@@ -201,3 +201,4 @@ Refuse to run DP on state spaces > 10⁷. Refuse to claim convergence without a
- [Bertsekas (2019). Reinforcement Learning and Optimal Control](http://www.athenasc.com/rlbook.html) — rigorous treatment of contraction-mapping arguments.
- [Puterman (2005). Markov Decision Processes](https://onlinelibrary.wiley.com/doi/book/10.1002/9780470316887) — modified policy iteration and its convergence analysis.
- [Howard (1960). Dynamic Programming and Markov Processes](https://mitpress.mit.edu/9780262582300/dynamic-programming-and-markov-processes/) — the original policy iteration paper.
- [Bertsekas & Tsitsiklis (1996). Neuro-Dynamic Programming](http://www.athenasc.com/ndpbook.html) — the bridge from DP to approximate-DP / deep RL used by every subsequent lesson.