Paper Citation Record · LEDGER

Online Competitive Information Gathering for Partially Observable Trajectory Games

As of 18 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2506.01927.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.01927 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:40:09.868243Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

verified exact1
verified fuzzy22
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d845588f-9336-4d0d-86b4-89f8b37f907c · outbound

This paper cites MIT Press, 2024.

Online Competitive Information Gathering for Partially Observable Trajectory Games MIT Press, 2024

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:58.052372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fca4374f-d281-4765-a598-2e441dbe33c8 · outbound

This paper cites Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning.

Online Competitive Information Gathering for Partially Observable Trajectory Games Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:39:47.380375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e3df3c1-19ce-4a5e-934e-342a8e8fdaa4 · outbound

This paper cites Springer, 2018.

Online Competitive Information Gathering for Partially Observable Trajectory Games Springer, 2018

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:57.908050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e1a024c3-66b4-490c-92ab-0c092a84dfe1 · outbound

This paper cites Bridging the Gap between Partially Observable Stochastic Games and Sparse POMDP Methods.

Online Competitive Information Gathering for Partially Observable Trajectory Games Bridging the Gap between Partially Observable Stochastic Games and Sparse POMDP Methods

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T11:39:47.566631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17fb916f-9394-46a2-883c-f2c9f9418daa · outbound

This paper cites Julia: A fresh approach to numerical computing.SIAM review, 59(1):65–98, 2017.

Online Competitive Information Gathering for Partially Observable Trajectory Games Julia: A fresh approach to numerical computing.SIAM review, 59(1):65–98, 2017

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:57.829313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fda21ea0-75dd-4caa-abe6-85479eb71b68 · outbound

This paper cites Deep counterfactual regret minimization.

Online Competitive Information Gathering for Partially Observable Trajectory Games Deep counterfactual regret minimization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:39:51.667355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e39fed7c-98d5-4de1-a85b-0f2a248f27d9 · outbound

This paper cites ALGAMES: A Fast Solver for Constrained Dynamic Games.

Online Competitive Information Gathering for Partially Observable Trajectory Games ALGAMES: A Fast Solver for Constrained Dynamic Games

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:40:10.032366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dd2b9ebd-3636-4082-9b55-e3d4d39552cf · outbound

This paper cites Interac- tive pomdps: Properties and preliminary results.

Online Competitive Information Gathering for Partially Observable Trajectory Games Interac- tive pomdps: Properties and preliminary results

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:57.755271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b339a653-310d-4e1a-a924-09810e93175b · outbound

This paper cites Learning others’ intentional models in multi-agent settings using interac- tive pomdps.Advances in Neural Information Processing Systems, 31, 2018.

Online Competitive Information Gathering for Partially Observable Trajectory Games Learning others’ intentional models in multi-agent settings using interac- tive pomdps.Advances in Neural Information Processing Systems, 31, 2018

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:57.514956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5426a82d-6cab-4e5a-aeb9-3d3ae4be1268 · outbound

This paper cites Deep Reinforcement Learning from Self-Play in Imperfect-Information Games.

Online Competitive Information Gathering for Partially Observable Trajectory Games Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T11:39:52.100527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cebeb383-717a-4b90-8f9a-c03c6fda6cad · outbound

This paper cites Flux: Elegant machine learning with julia.

Online Competitive Information Gathering for Partially Observable Trajectory Games Flux: Elegant machine learning with julia

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:55.994955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e3ae1e63-b8ad-482c-be52-b2d7a56f08f7 · outbound

This paper cites Rethinking formal models of partially observable multiagent decision making.Artifi- cial Intelligence, 303:103645, 2022.

Online Competitive Information Gathering for Partially Observable Trajectory Games Rethinking formal models of partially observable multiagent decision making.Artifi- cial Intelligence, 303:103645, 2022

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:55.869606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1ecec939-c349-4843-96ce-6c9937728db1 · outbound

This paper cites Multi-hypothesis interactions in game-theoretic motion planning.

Online Competitive Information Gathering for Partially Observable Trajectory Games Multi-hypothesis interactions in game-theoretic motion planning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:54.881763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9924e5bc-3649-43f7-8a0c-d9a1d81de9a6 · outbound

This paper cites A unified game-theoretic approach to multiagent reinforcement learning.Advances in neural information processing systems, 30, 2017.

Online Competitive Information Gathering for Partially Observable Trajectory Games A unified game-theoretic approach to multiagent reinforcement learning.Advances in neural information processing systems, 30, 2017

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:45.356992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 30fa4a22-ef9c-4158-9678-e83c042ef5e2 · outbound

This paper cites On gradient-based learning in continuous games.SIAM Journal on Mathematics of Data Science, 2(1):103–131, 2020.

Online Competitive Information Gathering for Partially Observable Trajectory Games On gradient-based learning in continuous games.SIAM Journal on Mathematics of Data Science, 2(1):103–131, 2020

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:36.022715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 75a8cfac-3420-4cc4-b8ca-a801bd2df9de · outbound

This paper cites XDO: A Double Oracle Algorithm for Extensive-Form Games.

Online Competitive Information Gathering for Partially Observable Trajectory Games XDO: A Double Oracle Algorithm for Extensive-Form Games

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:35.886313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ce6c373f-e282-4bf6-b728-e11e7d0e6bcf · outbound

This paper cites Mastering the game of stratego with model-free multi- agent reinforcement learning.Science, 378(6623):990– 996, 2022.

Online Competitive Information Gathering for Partially Observable Trajectory Games Mastering the game of stratego with model-free multi- agent reinforcement learning.Science, 378(6623):990– 996, 2022

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:34.930887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c1eecbc-ab72-43e7-a7bc-9579deba3396 · outbound

This paper cites Learn- ing mixed strategies in trajectory games.

Online Competitive Information Gathering for Partially Observable Trajectory Games Learn- ing mixed strategies in trajectory games

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:31.436635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 117816f2-8c0e-47f3-befa-8424c45f0994 · outbound

This paper cites Belief space planning assuming maximum likelihood observations.

Online Competitive Information Gathering for Partially Observable Trajectory Games Belief space planning assuming maximum likelihood observations

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:23.658211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5767c8fb-2929-4ffc-953b-8c7c72d8b8ee · outbound

This paper cites Information gathering actions over human internal state.

Online Competitive Information Gathering for Partially Observable Trajectory Games Information gathering actions over human internal state

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:23.082566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b2bdba09-f0e1-4b7e-9e7f-72e60d159f99 · outbound

This paper cites Theory of mind for a humanoid robot.

Online Competitive Information Gathering for Partially Observable Trajectory Games Theory of mind for a humanoid robot

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:12.226782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3d5ce6d6-75f2-49f1-b8a6-361f7c8af0cb · outbound

This paper cites Stochastic dynamic games in belief space.

Online Competitive Information Gathering for Partially Observable Trajectory Games Stochastic dynamic games in belief space

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:12.120079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0868ce87-1bd3-4f95-9fc6-b2fe47519b8c · outbound

This paper cites Online planning for interactive-pomdps using nested monte carlo tree search.

Online Competitive Information Gathering for Partially Observable Trajectory Games Online planning for interactive-pomdps using nested monte carlo tree search

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:12.061279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dde45a1e-afd1-4950-a66f-001ec74eb64d · outbound

This paper cites Solving heads-up limit texas hold’em.

Online Competitive Information Gathering for Partially Observable Trajectory Games Solving heads-up limit texas hold’em

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:12.011944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ba390389-8051-45fc-a6ef-a54c7ea9de51 · outbound

This paper cites Grandmaster level in starcraft ii using multi-agent reinforcement learning.nature, 575(7782): 350–354, 2019.

Online Competitive Information Gathering for Partially Observable Trajectory Games Grandmaster level in starcraft ii using multi-agent reinforcement learning.nature, 575(7782): 350–354, 2019

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:11.978528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bad90572-2f18-4873-a9fc-1713634acb8b · outbound

This paper cites On the computational complexity of stochastic controller optimization in pomdps.ACM Transactions on Compu- tation Theory (TOCT), 4(4):1–8, 2012.

Online Competitive Information Gathering for Partially Observable Trajectory Games On the computational complexity of stochastic controller optimization in pomdps.ACM Transactions on Compu- tation Theory (TOCT), 4(4):1–8, 2012

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:11.882563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9ed12615-01dc-49cc-ba31-33528f627695 · outbound

This paper cites Game theoretic motion planning for multi-robot racing.

Online Competitive Information Gathering for Partially Observable Trajectory Games Game theoretic motion planning for multi-robot racing

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:40:11.701192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3ef24ad3-e664-40b9-b56e-250c9a67d684 · outbound

This paper cites Game-Theoretic Multiagent Reinforcement Learning.

Online Competitive Information Gathering for Partially Observable Trajectory Games Game-Theoretic Multiagent Reinforcement Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T11:40:09.868243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.