**Overall Verdict:** Accept — The submission is complete, technically coherent, and end-to-end reachable, with public-answer retrieval risk requiring evaluator isolation.

**Completeness Check:**
- Instruction: Complete — The mathematical problem, assumptions, released output, and required numerical evaluability are clearly specified.
- Inputs: Complete — The solver-visible input is self-contained and matches the task description.
- Toolchain: Complete — Python 3.11 and SciPy 1.14 are free, compatible with Windows, and sufficient for evaluating the finite-dimensional optimization.
- Reference output: Complete — It provides the exact forward recursion, backward recursion, constraints, and Rényi-divergence objective required for objective comparison.
- Rubric: Complete — Mathematically equivalent formulations are accepted, while omission of the independent clipping branch or substitution of a heuristic approximation is explicitly identified as failure.

**File and Task Reachability:**
The attachment set is `reachable`, and the end-to-end task is `reachable`. All eight attachments were inspected. `ALE_input_materials.txt` (784 bytes), `ALE_reference_output.txt` (1,573 bytes), and `ale_dp_selftest.txt` (15,538 bytes) are readable UTF-8 text. `Screenshot-1.png` through `Screenshot-5.png` are valid, renderable, non-interlaced RGBA PNG images ranging from 2,809×924 to 2,872×1,675 pixels; their byte counts match the manifest. The screenshots and transcript consistently document the self-test’s looser derivation and its omission of the critical clipping-based branch. There are no archives, encryption barriers, missing objects, or unreviewed contents, and no material inspection limitations remained. The solver can derive a text answer and numerically evaluate the stated finite optimization on one ordinary machine; the evaluator can compare its recursions, constraints, and objective against the protected reference. The input, reference, and self-test evidence have distinct declared roles. License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.

**Special Screening:**
`public_benchmark` — The evaluator evidence identifies the protected result as an exact theorem from a named public paper, making the standard answer potentially retrievable. Keep the reference and verification metadata evaluator-only and use a network-isolated solver environment. The submitted evidence does not establish pervasive pretraining memorization.

**Recommended Changes:**
The task and reference correctly preserve the critical clipping branch and exact optimization, and no contributor revision is required. Evaluation should enforce separation of solver-visible inputs from the reference and disable external retrieval during solving. An optional notation cleanup could distinguish the convex domain from the scalar clipping radius, both currently denoted by \(K\).