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REVIEW 3 major objections 5 minor 28 references

Treasure Hunt in Anonymous Graphs with Quantum Pebbles by Oblivious Agents

T0 review · 3 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read A memoryless agent can find a treasure in an anonymous graph in D steps by measuring qubits emitted by quantum pebbles.

desk verdict A novel quantum-pebble encoding with a basically sound core protocol, but the headline measurement bound is off by a factor Δ/2 and several addressable gaps need cleaning. read the letter →

arxiv 2509.02909 v1 pith:BN4KSINO submitted 2025-09-03 quant-ph cs.DCcs.DScs.ET

Gaurav Gaur , Barun Gorain , Rishi Ranjan Singh , Daya Gaur This is my paper · ORCID
classification quant-phcs.DCcs.DScs.ET
keywords quantumpebblesanonymousgraphsobliviousagentstreasurehuntmeasurementportnumbersadvicecomplexitydistributedsearch
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper tries to show that an agent with no memory can still solve treasure hunt in anonymous graphs, where classical pebbles provably cannot guide an oblivious searcher, if each pebble is replaced by a quantum source that repeatedly emits the same unknown qubit state. The agent does not need to remember anything: at each node it performs repeated measurements of emitted qubits in several rotated bases, and the only basis that yields a deterministic outcome tells it which port to take. The claimed result is that D quantum pebbles placed along a shortest path let the agent reach a treasure at distance D in exactly D moves, with O((log D + log Delta)/(log 1/delta)) measurements per node and high success probability. If true, this would be the first constructive role for quantum information as a navigation aid in anonymous distributed search, and a way around a classical impossibility.

What carries the argument

The load-bearing object is a family of measurement bases M(j) = {(|0> + e^{ij phi}|1>)/sqrt(2), (|0> - e^{ij phi}|1>)/sqrt(2)} for j = 0, ..., Delta/2 - 1, with phi = pi/Delta. Port number 2i+1 is encoded as |i+> and port number 2i+2 as |i->. A qubit in one of these states, measured in its own basis, gives a deterministic outcome; measured in any other basis it gives each outcome with probability at most delta = cos^2(pi/(2 Delta)). Repeated measurement in all bases therefore identifies the port number, and the emitter-based quantum pebble supplies the many identical copies needed for the repeated trials.

What would settle it

Prepare a qubit in one of the four states used for degree-4 graphs, measure it n times in a wrong basis, and count how often all n outcomes agree. The paper's general bound treats this ambiguity as at most cos^2(pi/8)^n, while the degree-4 section uses 2^{-n}; an experiment measuring the actual rate of ambiguous runs would settle which bound governs and therefore whether the promised measurement count per node is correct.

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Extended reading notes

Core claim

The paper's central claim is Theorem 3: there is a randomized strategy, using at most one quantum pebble per node on the shortest path—D pebbles total—that lets an oblivious agent find the treasure in D steps. The oracle encodes the port number of the next edge as one of Delta/2 two-dimensional bases: port 2i+1 is the state |i+> and port 2i+2 is |i->. The agent measures emitted qubits n times in every basis. In the single correct basis the outcome is deterministic; in each wrong basis, a run of n identical outcomes that could mislead the agent has probability at most delta^n, with delta = cos^2(pi/(2 Delta)), and union-bounding over the wrong bases gives per-node failure probability at most

Load-bearing premise

The load-bearing premise is that a quantum pebble is an unlimited source that keeps emitting qubits in the same fixed, unknown state, so the agent can take as many identical copies as it wants; if emissions are finite, noisy, or the state drifts, the measurement budget and the D-step guarantee no longer follow.

Editorial extensions

If this is right

  • An oblivious agent can navigate a precomputed shortest path in anonymous graphs, making only local look-measure-move decisions, with no memory of earlier rounds.
  • D quantum pebbles suffice for a high-probability treasure hunt in D steps, matching the shortest-path lower bound in time.
  • The quantum protocol is strictly more expressive than classical pebbles for oblivious agents: the classical one-bit presence signal is provably insufficient, while the quantum state carries a port choice.
  • The per-node measurement budget grows only logarithmically in D and Delta (up to the 1/log(1/delta) factor), so the dominant cost stays linear in the distance.
  • A single-pebble encoding of the whole path is not a shortcut; it requires exponentially many bases and is provably no faster than the per-node encoding.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A direct test of the idea: if the pebble emitted a classical bit string rather than identical qubits, the agent would need to remember earlier bits to form the string; identical quantum states are what make repeated measurements a memoryless decoder, suggesting the same trick could replace memory in other state-estimation tasks.
  • The paper works with two-outcome projective measurements; using a qudit or a POVM with more outcomes would cut the measurement count, pointing to a resource tradeoff between pebble dimension and agent measurement time.
  • The authors' own remark that the angle bound is pessimistic implies n could be reduced by tracking the actual basis separations; an improved analysis of the bounding lemma would strengthen the theorem without changing the protocol.
  • Since the oracle must know the shortest path and place pebbles, the quantum advantage is in the guidance channel, not in discovering the path; the method would combine naturally with any path-finding preprocessing.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. The paper studies treasure hunt in anonymous graphs (unlabeled vertices, port-labeled edges) by an oblivious agent. It first proves (Theorem 1) that deterministic strategies using classical pebbles cannot guide an oblivious agent to a treasure. It then introduces 'quantum pebbles,' idealized sources that repeatedly emit qubits in a fixed but unknown state, and proposes a protocol in which an oracle places one quantum pebble on each vertex of a shortest s-t path. The pebble at a vertex encodes the next port number in the qubit state; the agent measures the emitted qubits in several bases and, with high probability, decodes the correct port. The paper develops the construction for Δ=4 (Section 3) and for general maximum degree Δ (Section 4), proving Theorem 3: a randomized strategy using D quantum pebbles finds the treasure in D steps and uses O((log D + log Δ)/log(1/δ)) measurements per node, where δ = cos²(π/(2Δ)). A final remark argues that encoding the whole path in one qubit is not more efficient. The claimed D-step traversal time is correct in spirit, but the quantitative measurement bound stated in the abstract, Theorem 3, and conclusion is missing a factor of Δ/2 that the protocol itself requires.

Significance. If the main claim held as stated, the paper would contribute a genuinely novel use of quantum information as a distributed advice mechanism: a memoryless agent could follow a precomputed shortest path by decoding port numbers from repeated measurements of identical qubits, something impossible with classical pebbles. The paper's strengths are its self-contained protocol, the explicit construction of the measurement bases, and the elementary union-bound analysis of the decoding error. The central decoding idea (Lemmas 3 and 4) is sound. However, the headline quantitative contribution is overstated by a factor of Δ/2, and after the correct accounting the per-node measurement bound is O(Δ(log D + log Δ)/log(1/δ)) = O(Δ³(log D + log Δ)), not O((log D + log Δ)/log(1/δ)) = O(Δ²(log D + log Δ)). The protocol also has a formal inconsistency in port numbering, and Remark 3 cites nonexistent theorem/lemma numbers. The idealized infinite-copy emitter is a modeling assumption that should be stated more carefully, but it is not internally inconsistent.

major comments (3)
  1. [Section 4.2 and Theorem 3] The paper's own accounting gives the per-node measurement cost as nΔ/2, not n. Section 4.2 states: 'the agent at node v measures the qubits emitted from the quantum pebble at v, n times in each of the M^(j) basis. This requires a total of nΔ/2 measurements at each node.' Yet Theorem 3 and the abstract state that the agent makes O((log D + log Δ)/log(1/δ)) measurements per node, and the proof of Theorem 3 chooses n = O((log D + log Δ)/log(1/δ)). If n is measurements per basis, the per-node cost is (Δ/2)n = O(Δ(log D + log Δ)/log(1/δ)). If n is instead intended as the total number of measurements, then the failure-probability calculation must use n/(Δ/2) measurements per basis; solving Δδ^(n/(Δ/2)) ≤ 1/D again gives n = O(Δ(log D + log Δ)/log(1/δ)). Thus the stated bound is wrong by a factor of Δ/2 either way. Since log(1/δ) = Θ(1/Δ²), the claimed bound is O(Δ²(log D + log Δ)) while the pr
  2. [Section 1 vs. Section 3.2/4.2] The model in Section 1 defines port numbers in the range [0:deg(v)-1], but the encoding in Section 3.2 uses port numbers 1,2,3,4 for Δ=4, and the general encoding f(j) in Section 4.2 maps port numbers 1,...,Δ (with the example '1,4,3,2,4,1'). As written, the protocol cannot handle port 0, which is a valid port in the stated model. This is a formal correctness gap in the presented algorithm. The fix is straightforward—either revise the model to say ports are 1,...,deg(v), or shift the encoding so that port 0 is handled—but the discrepancy should be addressed explicitly.
  3. [Remark 3] Remark 3 claims that encoding the entire path in a single quantum pebble is not more efficient, and the conclusion lists this as a proven contribution. However, the argument cites 'Theorem 9,' 'Lemma 7,' and 'Lemma 11,' none of which exist in the manuscript (the relevant results are Theorem 3, Lemma 4, and Lemma 5). The proof also conflates Δ^D (the number of paths) with ΔD (used in the angle and bounds in Lemma 5), and it does not rigorously justify why the number of required bases is Δ^D/2. Because the secondary claim is presented as a proof, the missing references and notation errors make it unverifiable. This should be repaired or the remark downgraded to a conjecture.
minor comments (5)
  1. [Theorem 3 statement] The phrase 'δ is an upper bound on the probability that the correct state is observed when measured in a particular basis' is misleading. In Lemma 4, δ bounds the probability of obtaining a definite-looking outcome when measuring a state from a different basis (i.e., a wrong-basis outcome), not the probability of observing the correct state. Please rephrase for clarity.
  2. [Lemma 2] The proof says measurements are taken 'n + 1 times' but the protocol and theorem use n; the notation should be harmonized. Also 'faliure' is a typo.
  3. [Throughout] Several typos and spacing issues: 'a a total of D quantum pebbles' in Theorem 3; 'port-node' instead of 'port number'; 'cos 2' without a superscript in the proof of Theorem 3; 'only of the the measurements' in Lemma 1. A careful proofreading pass is needed.
  4. [Definition 1 / Section 3.2] The emitter model assumes the quantum pebble can produce arbitrarily many fresh qubits in the same unknown state without being depleted or disturbed by measurements. This is an idealized assumption; the paper acknowledges decoherence but could more explicitly state that the analysis is in a noiseless, infinite-copy source model and that a physical implementation or error model is left open.
  5. [Section 3.2] The sentence 'the agent can take as many measurements as needed' is important because it is what avoids a no-cloning obstruction; it could be highlighted as a modeling assumption rather than an aside.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the main protocol derives its measurement bound from quantum-mechanical state-discrimination probabilities, and the oracle advice is explicit, not disguised as a prediction.

full rationale

The paper's derivation chain is self-contained. The oracle explicitly precomputes the shortest path and places D quantum pebbles whose states encode the next port number; the agent's task is to decode this advice by repeated measurements (Section 3.3 and Section 4.2). Theorem 3's measurement bound is obtained from Lemma 4, which upper-bounds the probability of confusing two basis states by cos²(π/2Δ), and then from a union-bound argument setting Δδⁿ ≤ 1/D. This is a standard probabilistic calculation from the Born rule, not a fitting of parameters from the target result. The only author-overlapping citations ([4], [13]) are background on pebble-guided search and are not load-bearing for the new protocol; the classical impossibility result is proven in-paper (Theorem 1), and the basis construction is standard and cited to a textbook ([21]). Even the skeptic's noted factor-Δ/2 discrepancy between Theorem 3's n and Section 4.2's nΔ/2 total measurements is a quantitative correctness issue in the claimed asymptotic efficiency, not a circularity: both readings still derive n from the same δ^m failure probability. No equation reduces to its own input, no fitted quantity is renamed a prediction, and no uniqueness theorem is imported from prior work by the same authors. Thus the protocol and its analysis are not circular.

Assumptions & free parameters 1 free parameters · 6 assumptions · 1 invented entities

The protocol rests on an idealized quantum emitter, standard measurement postulates, and several unproved conventions (even Delta, port numbering starting at 1). These are not fitted to data; they are modeling choices. The main algorithm parameter n is chosen to hit a failure target.

free parameters (1)
  • n (measurements per basis) = O((log D + log Delta)/log(1/delta))
    Hand-chosen sample count to make per-node failure probability Delta*delta^n = O(1/D); the constant is unspecified. It is an algorithm parameter, not fitted to data.
assumptions (6)
  • domain assumption A quantum pebble is an ideal emitter of an unlimited supply of identical copies of the same single-qubit state.
    Section 3.2 Definition 1 and Protocol step 2; without fresh copies, repeated measurements are impossible.
  • standard math Projective measurements obey the Born rule and collapse the state to a basis vector.
    Used in Lemmas 3 and 4 and Section 3.1; standard quantum mechanics from [21].
  • ad hoc to paper Maximum degree Delta can be assumed even without loss of generality.
    Section 4.1 states this without proof; no reduction for odd Delta is supplied.
  • domain assumption The agent knows D and can read local port labels and pebble presence during the look phase.
    Section 1 model; standard for treasure hunt with advice.
  • domain assumption The oracle knows the shortest path and can place a pebble with the exact encoding at each path node.
    Protocol step 1; this is the advice model, not derived from the agent's capabilities.
  • domain assumption The agent can map measurement outcome labels (j+, j-) to port numbers via f inverse.
    Protocol in Section 4.2; requires an agreed convention, which conflicts with the port-0 model.
invented entities (1)
  • Quantum pebble (single-state qubit emitter)
    purpose: Stationary advice device placed at each shortest-path node; emits identical qubits encoding the outgoing port toward the treasure
    Theoretical device only. The paper gives no experimental signature or implementation proposal; it says 'we hope the technology will sufficiently advance'. No falsifiable handle outside the paper.

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Pith. "Pith review of Treasure Hunt in Anonymous Graphs with Quantum Pebbles by Oblivious Agents." pith.science (2026). https://pith.science/paper/BN4KSINO

@misc{pith2026250902909,
  author       = {Pith},
  title        = {Pith review of: Treasure Hunt in Anonymous Graphs with Quantum Pebbles by Oblivious Agents},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/BN4KSINO}},
  note         = {Machine review of arXiv:2509.02909}
}
abstract

We investigate the problem of finding a static treasure in anonymous graphs using oblivious agents and introduce a novel approach that leverages quantum information. In anonymous graphs, vertices are unlabelled, indistinguishable, and edges are locally labelled with port numbers. Agents typically rely on stationary classical pebbles placed by an oracle to guide their search. However, this classical approach is constrained by limited information transmission and high traversal complexity. Classical pebbles are not sufficient for search if the agents are oblivious. We propose the first use of quantum pebbles for search in anonymous graphs. Quantum pebbles periodically emit qubits in a fixed quantum state. Each pebble encodes the port number to the next node using a unique quantum state. The agent determines the correct path by performing measurements in multiple bases, exploiting the probabilistic nature of quantum measurement to distinguish states. We show that this strategy enables an oblivious agent to locate the treasure in $D$ steps using $D$ quantum pebbles, where $D$ is the length of the shortest path between the starting point and the treasure. Moreover, only $O((\log D + \log \Delta)/(\log 1/\delta))$ measurements per node are required to ensure high success probability in a graph with maximum degree $\Delta$ where $\delta = \cos^2(\frac{\pi}{2\Delta})$. We propose the use of quantum information as a guidance mechanism in anonymous graph search. We demonstrate that quantum pebbles can not only emulate the functionality of classical pebbles but can do so with improved efficiency, offering a promising direction for future quantum-enhanced distributed algorithms.

Figures

Figures reproduced from arXiv: 2509.02909 by the authors.

Figure 1
Figure 1. The Graph Gpqr, where p, q, r ∈ {0, 1, 2} and distinct. pebble at a node with degree 3 and hence takes port 0 and reaches node V . If a pebble is present at V , then the agent returns to U via port 1 in the next round, and then the movement from U to V and then V to U goes on indefinitely, and therefore, the agent can never find the treasure. Otherwise, the agent takes port 0 and returns to S, and the process is rep… view at source ↗
Figure 2
Figure 2. The vectors |0+⟩, |0−⟩ form basis M(0) and |1+⟩, |1−⟩ form basis M(1) when the maximum degree ∆ = 4. The four vectors are plotted on the Bloch sphere using their polar representation given above. the outcome corresponding to |j−⟩ is |β| 2 = |⟨j−|ψ⟩|2 . After measurement, the state of the qubit collapses to the corresponding basis state: if the outcome corresponded to |j+⟩, the state becomes |j+⟩; if it corresponded … view at source ↗

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Reference graph

Works this paper leans on

28 extracted references · 28 canonical work pages

  1. [1]

    Alpern, S., Gal, S.: The theory of search games and rendezvous, vol. 55. Springer Science & Business Media (2006)

    work page 2006

  2. [2]

    In: Oshman, R

    Bampas, E., Beauquier, J., Burman, J., Guy-Obé, W.: Treasure hunt with volatile pheromones. In: Oshman, R. (ed.) 37th Inter- national Symposium on Distributed Computing, DISC 2023, October 10-12, 2023, L’Aquila, Italy. LIPIcs, vol. 281, pp. 8:1–8:21 (2023). https://doi.org/10.4230/LIPICS.DISC.2023.8

    work page doi:10.4230/lipics.disc.2023.8 2023

  3. [3]

    In: Proceedings of the thirtieth annual ACM symposium on Theory of computing

    Bender, M.A., Fernández, A., Ron, D., Sahai, A., Vadhan, S.: The power of a pebble: Exploring and mapping directed graphs. In: Proceedings of the thirtieth annual ACM symposium on Theory of computing. pp. 269–278 (1998)

    work page 1998

  4. [4]

    In: Networked Systems - 11th International Conference, NETYS 2023, Benguerir, Morocco

    Bhattacharya, A., Gorain, B., Mandal, P.S.: Pebble guided treasure hunt in plane. In: Networked Systems - 11th International Conference, NETYS 2023, Benguerir, Morocco. Lecture Notes in Computer Science, vol. 14067, pp. 141–156. Springer (2023)

    work page 2023

  5. [5]

    In: International Colloquium on Struc- tural Information and Communication Complexity

    Böckenhauer, H.J., Frei, F., Unger, W., Wehner, D.: Zero-memory graph exploration with unknown inports. In: International Colloquium on Struc- tural Information and Communication Complexity. pp. 246–261. Springer (2023) 19

    work page 2023

  6. [6]

    In: Algorithms–ESA 2013: 21st Annual European Sympo- sium, Sophia Antipolis, France, September 2-4, 2013

    Bose, P., De Carufel, J.L., Durocher, S.: Revisiting the problem of search- ing on a line. In: Algorithms–ESA 2013: 21st Annual European Sympo- sium, Sophia Antipolis, France, September 2-4, 2013. Proceedings 21. pp. 205–216. Springer (2013)

    work page 2013

  7. [7]

    ACM Transactions on Al- gorithms 19(3), 1–32 (2023)

    Bouchard, S., Dieudonné, Y., Labourel, A., Pelc, A.: Almost-optimal de- terministic treasure hunt in unweighted graphs. ACM Transactions on Al- gorithms 19(3), 1–32 (2023)

    work page 2023

  8. [8]

    Algorithmica82, 3250–3281 (2020)

    Bouchard, S., Dieudonné, Y., Pelc, A., Petit, F.: Deterministic treasure hunt in the plane with angular hints. Algorithmica82, 3250–3281 (2020)

    work page 2020

Show all 28 references
  1. [9]

    Nature Physics5(1), 19– 26 (2009)

    Briegel, H.J., Browne, D.E., Dür, W., Raussendorf, R., Van den Nest, M.: Measurement-based quantum computation. Nature Physics5(1), 19– 26 (2009)

    2009

  2. [10]

    PeerJ Computer Science7, e466 (2021)

    Das, S., Di Luna, G.A., Mazzei, D., Prencipe, G.: Compacting oblivious agents on dynamic rings. PeerJ Computer Science7, e466 (2021)

    2021

  3. [11]

    Dudek, G., Jenkin, M., Milios, E., Wilkes, D.: Robotic exploration as graph construction. J. Comput., vol7(3) (1978)

    1978

  4. [12]

    Algorith- mica 65, 562–583 (2013)

    Flocchini, P., Ilcinkas, D., Pelc, A., Santoro, N.: Computing without com- municating: Ring exploration by asynchronous oblivious robots. Algorith- mica 65, 562–583 (2013)

    2013

  5. [13]

    Theoretical Computer Science922, 61–80 (2022)

    Gorain, B., Mondal, K., Nayak, H., Pandit, S.: Pebble guided optimal treasure hunt in anonymous graphs. Theoretical Computer Science922, 61–80 (2022)

    2022

  6. [14]

    Ilcinkas, D.: Structural information in distributed computing. Ph.D. thesis, Université de Bordeaux (UB) (2019)

    2019

  7. [15]

    Information and computation131(1), 63–79 (1996)

    Kao, M.Y., Reif, J.H., Tate, S.R.: Searching in an unknown environment: An optimal randomized algorithm for the cow-path problem. Information and computation131(1), 63–79 (1996)

    1996

  8. [16]

    In: International Colloquium on Structural Information and Commu- nication Complexity

    Komm, D., Královič, R., Královič, R., Smula, J.: Treasure hunt with ad- vice. In: International Colloquium on Structural Information and Commu- nication Complexity. pp. 328–341. Springer (2015)

    2015

  9. [17]

    In: Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms

    Langetepe, E.: On the optimality of spiral search. In: Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms. pp. 1–12. SIAM (2010)

    2010

  10. [18]

    Journal of Parallel and Distributed Computing83, 159– 167 (2015)

    Miller, A., Pelc, A.: Tradeoffs between cost and information for rendezvous and treasure hunt. Journal of Parallel and Distributed Computing83, 159– 167 (2015)

    2015

  11. [19]

    Physics Letters A308(2-3), 96–100 (2003) 20

    Nielsen, M.A.: Quantum computation by measurement and quantum mem- ory. Physics Letters A308(2-3), 96–100 (2003) 20

    2003

  12. [20]

    Physical Review Letters79(2), 321 (1997)

    Nielsen, M.A., Chuang, I.L.: Programmable quantum gate arrays. Physical Review Letters79(2), 321 (1997)

    1997

  13. [21]

    Cambridge university press (2010)

    Nielsen, M.A., Chuang, I.L.: Quantum computation and quantum infor- mation. Cambridge university press (2010)

    2010

  14. [22]

    Discrete Applied Mathematics356, 149–160 (2024)

    Pattanayak, D., Pelc, A.: Graph exploration by a deterministic memory- less automaton with pebbles. Discrete Applied Mathematics356, 149–160 (2024)

    2024

  15. [23]

    Information Processing Letters140, 13–17 (2018)

    Pelc, A.: Reaching a target in the plane with no information. Information Processing Letters140, 13–17 (2018)

    2018

  16. [24]

    information tradeoffs for treasure hunt in the plane

    Pelc, A., Yadav, R.N.: Cost vs. information tradeoffs for treasure hunt in the plane. arXiv preprint arXiv:1902.06090 (2019)

    1902 arXiv

  17. [25]

    Information and Computation281, 104705 (2021)

    Pelc, A., Yadav, R.N.: Advice complexity of treasure hunt in geometric terrains. Information and Computation281, 104705 (2021)

    2021

  18. [26]

    Physical review letters86(22), 5188 (2001)

    Raussendorf, R., Briegel, H.J.: A one-way quantum computer. Physical review letters86(22), 5188 (2001)

    2001

  19. [27]

    arXiv preprint arXiv:2505.02789 (2025)

    Takahashi, S., Kanaya, H., Hiraoka, S., Eguchi, R., Sudo, Y.: Recolorable graph exploration by an oblivious agent with fewer colors. arXiv preprint arXiv:2505.02789 (2025)

    2025 arXiv

  20. [28]

    In: International Symposium on Algorithms and Computation

    Xin, Q.: Faster treasure hunt and better strongly universal exploration sequences. In: International Symposium on Algorithms and Computation. pp. 549–560. Springer (2007) 21

    2007

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