The value of Robbins' problem is larger than 2
Authors/Creators
Description
This is AI-generated research: the results, proofs and code were found and written by AI. Credit goes to all the humans whose work it builds on.
Robbins' problem asks for the least expected rank $V(n)$ of a value selected by a stopping rule from $n$ independent uniform values shown one at a time, with full information, and for its limit $V$. We prove that $V(n)>2.0038$ for every $n\ge300$, so that $V>2$. This answers a question of Bruss and Ferguson, who asked in 1996 whether $V>2$. The proof relaxes the problem to one in which only the five smallest values seen are remembered and each value that leaves the memory is charged the probability that all later values exceed it. A lower bound for the relaxed problem with $300$ values is certified by finite tables of values and slopes on geometric grids, in exact integer arithmetic. The proof is computer-assisted, and the whole of it, the check of the certificate included, is formalized in Lean 4 with Mathlib.
The question is the one of p. 7 of F. T. Bruss and T. S. Ferguson, Half-prophets and Robbins' problem of minimizing the expected rank, Lecture Notes in Statist. 114 (1996), and of Section 8 of F. T. Bruss, What is known about Robbins' problem?, J. Appl. Probab. 42 (2005).
The bound on $V(n)$ for every $n\ge300$ is proved in Lean 4 with Mathlib with no hypothesis, and the bound on $V$ for every limit of the sequence $V(n)$, both with only the standard axioms. The tables of the certificate, written by a Rust program, are checked by the Lean kernel inside the formal proof.
Code, Lean proofs and certificates: github.com/mt0-svg/robbins-problem
Files
robbins.pdf
Additional details
Related works
- Is supplemented by
- https://github.com/mt0-svg/robbins-problem (URL)
- References
- 10.1007/978-1-4612-0749-8_1 (DOI)
- 10.1239/jap/1110381374 (DOI)
References
- 311859884+mt0-svg@users.noreply.github.com. The value of Robbins' problem is larger than 2. Lean 4 formalization, Lean 4.34.1 and Mathlib v4.34.1, https://github.com/mt0-svg/robbins-problem, 2026.
- D. Assaf and E. Samuel-Cahn. The secretary problem: minimizing the expected rank with i.i.d. random variables. Adv. in Appl. Probab., 28(3):828-852, 1996. doi:10.2307/1428183.
- C. Bailey. nanoda: an external type checker for Lean 4. Rust program, https://github.com/ammkrn/nanoda_lib, commit 3a2407216ee84a75f9e1aead6803d0578be06ae7, 2026.
- L. Brice, F. T. Bruss, A. Majumdar, and J.-F. Raskin. Algorithms for Robbins' problem using Markov decision processes. In Principles of Verification: Cycling the Probabilistic Landscape, Lecture Notes in Comput. Sci. 15261, pages 18-45. Springer, Cham, 2025. doi:10.1007/978-3-031-75775-4_2.
- L. Brice, F. T. Bruss, A. Majumdar, and J.-F. Raskin. Algorithms for Robbins' problem using Markov decision processes, extended version. arXiv:2608.27419, 2026.
- F. T. Bruss. What is known about Robbins' problem? J. Appl. Probab., 42(1):108-120, 2005. doi:10.1239/jap/1110381374.
- F. T. Bruss. Deep learning and Robbins' problem. Newsletter of the Royal Statistical Society of Belgium, May 2022. https://rssb.be/wp-content/uploads/2022/05/RSSB-Bruss2022Robbins.pdf
- F. T. Bruss and T. S. Ferguson. Minimizing the expected rank with full information. J. Appl. Probab., 30(3):616-626, 1993. doi:10.2307/3214770.
- F. T. Bruss and T. S. Ferguson. Half-prophets and Robbins' problem of minimizing the expected rank. In C. C. Heyde, Yu. V. Prohorov, R. Pyke, and S. T. Rachev, editors, Athens Conference on Applied Probability and Time Series Analysis, Vol. I, volume 114 of Lecture Notes in Statist., pages 1-17. Springer, New York, 1996. doi:10.1007/978-1-4612-0749-8_1.
- F. T. Bruss and Y. C. Swan. A continuous-time approach to Robbins' problem of minimizing the expected rank. J. Appl. Probab., 46(1):1-18, 2009. doi:10.1239/jap/1238592113.
- L. de Moura and S. Ullrich. The Lean 4 theorem prover and programming language. In Automated Deduction, CADE 28, volume 12699 of Lecture Notes in Comput. Sci., pages 625-635. Springer, Cham, 2021. doi:10.1007/978-3-030-79876-5_37.
- R. Dendievel and Y. Swan. One step further: an explicit solution to Robbins' problem when n=4. Math. Appl. (Warsaw), 44(1), 2016. doi:10.14708/ma.v44i1.1138. arXiv:1601.07949.
- M. Meier and L. Sögner. A new strategy for Robbins' problem of optimal stopping. J. Appl. Probab., 54(1):331-336, 2017. doi:10.1017/jpr.2016.103.
- Y.-C. Swan. On two unsolved problems in probability. PhD thesis, Université Libre de Bruxelles, 2007. https://hdl.handle.net/2268/188656.
- The Comparator contributors. Comparator: a judge for Lean proofs. https://github.com/leanprover/comparator, commit d03acab154d269c06e60e4de7e4cc85deebff94b, 2026.
- The mathlib Community. The Lean mathematical library. In Proceedings of the 9th ACM SIGPLAN International Conference on Certified Programs and Proofs (CPP 2020), pages 367-381. ACM, New York, 2020. doi:10.1145/3372885.3373824.