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SamuelSchlesinger merged 3 commits into from
Oct 31, 2026
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doc(roadmap): drop the landed paging clients and the landed submodular greedy #1992

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doc(roadmap): drop the landed paging clients and the landed submodula…
SamuelSchlesinger Oct 31, 2026
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Merge remote-tracking branch 'origin/main' into claude/roadmap-submod…
SamuelSchlesinger Oct 31, 2026
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doc(roadmap): unlink the closed sparse-sets issue from the Meyer item
SamuelSchlesinger Oct 31, 2026
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11 changes: 4 additions & 7 deletions ROADMAP.md
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Expand Up @@ -202,7 +202,7 @@ index links to canonical definitions rather than keeping a second set.
- **Reducibilities** ([#1351]): logspace Turing reductions, in an oracle model whose query tape is
not charged to the space bound, and their transitivity; the rest of the inclusion hierarchy of
Ladner, Lynch and Selman, and its separations.
- **Sparse and tally sets** ([#1819]): `P/poly = P^SPARSE` (Meyer), extending
- **Sparse and tally sets:** `P/poly = P^SPARSE` (Meyer), extending
`PPoly.of_sparse` in `Circuit/Boolean/Sparse.lean`.
- **Berman–Hartmanis:** p-isomorphism and paddability; paddable NP-complete sets are p-isomorphic,
so the standard NP-complete problems are all p-isomorphic to SAT; the isomorphism conjecture as a
Expand Down Expand Up @@ -503,17 +503,15 @@ reusing graph and matroid foundations and the shared data-structure interfaces.
- **Spanning trees and matroids:** minimum spanning trees with sorting and disjoint-set costs;
weighted matroid greedy optimality with an independence-oracle interface; then matroid
intersection with explicit oracle and implementation costs.
- **Submodular optimization:** the `1 - 1/e` approximation for nonnegative monotone submodular
maximization under a cardinality constraint, charging value-oracle calls separately from their
concrete realizations; then further constraints and approximation bounds.
- **Submodular optimization:** further constraints and approximation bounds beyond the
cardinality-constrained `1 - 1/e` greedy, charging value-oracle calls separately from their
concrete realizations.

### Online algorithms and competitive analysis

- Request sequences, online strategies, offline optima and competitive ratios with additive
constants; distinguish deterministic and randomized strategies and oblivious and adaptive
adversaries. Compare algorithms in the same action and cost model, including initialization.
- **Paging:** an LRU competitive bound and a matching deterministic lower bound as the first
clients. Reuse native amortized certificates and make adversarial request generation explicit.
- **Adaptive search trees:** a BST access-and-rotation model, the splay access lemma, static
optimality, working-set and dynamic-finger bounds, and Wilber-style lower bounds. State dynamic
optimality as a conjectural research target with explicit strategy and sequence quantifiers.
Expand Down Expand Up @@ -868,5 +866,4 @@ not planned, not as proved.
[#1524]: https://github.com/cslib-community/complexitylib/issues/1524
[#1572]: https://github.com/cslib-community/complexitylib/issues/1572
[#1817]: https://github.com/cslib-community/complexitylib/issues/1817
[#1819]: https://github.com/cslib-community/complexitylib/issues/1819
[#1824]: https://github.com/cslib-community/complexitylib/issues/1824
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