Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:34:32.435835Z
Paper Citation Record · LEDGER
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
As of 20 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2506.15856.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
25 of 25 outbound references displayed
- verified exact1
- verified fuzzy22
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 8f531a07-aa77-45b2-b60b-98872ecd42d3 · outbound
This paper cites Threshold bandits, with and without cen- sored feedback.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Threshold bandits, with and without cen- sored feedback
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.962137Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e3315ede-c7fb-4eaa-813a-db83957c31df · outbound
This paper cites Asymptotically efficient adaptive allocation rules.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Asymptotically efficient adaptive allocation rules
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.759844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8665debe-a4a6-4909-9f16-b3ce5c53a68b · outbound
This paper cites On distributed cooperative decision-making in multiarmed bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework On distributed cooperative decision-making in multiarmed bandits
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.717408Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b747bd04-cc0f-4a93-b293-898c383c476c · outbound
This paper cites Social imitation in coopera- tive multiarmed bandits: Partition-based algorithms with strictly local information.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Social imitation in coopera- tive multiarmed bandits: Partition-based algorithms with strictly local information
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.699203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cd592c1f-edc7-412c-a330-3b2c5d319825 · outbound
This paper cites Bandit algorithms.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Bandit algorithms
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.662968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5c40fdaa-0b59-461e-84b6-268bd0b0a603 · outbound
This paper cites Decentralized Cooperative Stochastic Bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Decentralized Cooperative Stochastic Bandits
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:34:32.413143Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49cdaa70-c173-42a8-b78c-6b395fcafe73 · outbound
This paper cites Multi-player bandits–a musical chairs approach.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Multi-player bandits–a musical chairs approach
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.602166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d14454d1-750a-49ed-9977-7134ddc88cbd · outbound
This paper cites Balanced and incentivized learning with limited shared information in multi-agent multi-armed bandit.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Balanced and incentivized learning with limited shared information in multi-agent multi-armed bandit
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.583749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f02470dc-7acb-4bc4-843f-e619ae8530c0 · outbound
This paper cites Multi-Player Multi-Armed Bandits with Finite Shareable Resources Arms: Learning Algorithms & Applications.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Multi-Player Multi-Armed Bandits with Finite Shareable Resources Arms: Learning Algorithms & Applications
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T19:34:32.496701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8ea434fa-7a54-46c3-bbbb-cf86ae413172 · outbound
This paper cites Decentralized learning for multiplayer multiarmed bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Decentralized learning for multiplayer multiarmed bandits
Reference 1979
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.777775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fb96419b-bb2d-4651-8f75-64a72f6de0ff · outbound
This paper cites Bayesian algorithms for decentralized stochas- tic bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Bayesian algorithms for decentralized stochas- tic bandits
Reference 1985
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.737730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ba844463-ca94-48d4-9eff-2e95db99653a · outbound
This paper cites Finite-time analysis of the multiarmed bandit problem.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Finite-time analysis of the multiarmed bandit problem
Reference 1995
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.908689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c09d8a75-f1d4-42f5-9713-31f83bdecde9 · outbound
This paper cites Communicating with unknown teammates.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Communicating with unknown teammates
Reference 2002
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.889492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 6a4e4c08-f5c3-4fac-83ca-ef26f51c5649 · outbound
This paper cites Decentralized heterogeneous multi- player multi-armed bandits with non-zero rewards on collisions.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Decentralized heterogeneous multi- player multi-armed bandits with non-zero rewards on collisions
Reference 2010
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.621530Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8f2f8cbd-1210-40cf-af60-0ef5947bc0e0 · outbound
This paper cites Coordinated versus decentralized exploration in multi- agent multi-armed bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Coordinated versus decentralized exploration in multi- agent multi-armed bandits
Reference 2012
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.816167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b08c4370-9e0b-49cf-8dca-188470a98880 · outbound
This paper cites Game of thrones: Fully distributed learning for multi- player bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Game of thrones: Fully distributed learning for multi- player bandits
Reference 2014
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.872045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5b6723f9-ee7f-4168-a16f-7adedc730406 · outbound
This paper cites Multi-agent multi-armed bandits with limited communication.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Multi-agent multi-armed bandits with limited communication
Reference 2016
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.945226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation bf4a7aca-b7d9-4bdf-874d-60d88e9f27d5 · outbound
This paper cites Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:34:32.352464Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 47774e1c-d879-4c1c-aff5-dd156cc021d3 · outbound
This paper cites Distributed cooperative deci- sion making in multi-agent multi-armed bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Distributed cooperative deci- sion making in multi-agent multi-armed bandits
Reference 2018
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.680991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 90557fa2-6e8d-48d5-8601-8cda7787345a · outbound
This paper cites Regret analysis of stochastic and nonstochastic multi-armed bandit problems.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Regret analysis of stochastic and nonstochastic multi-armed bandit problems
Reference 2019
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.836025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d3d053b0-c22d-45ca-89d6-a455e00d2949 · outbound
This paper cites Distributed learning in multi-armed bandit with multiple players.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Distributed learning in multi-armed bandit with multiple players
Reference 2020
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.642473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 91536ef5-ece8-4479-ab15-46bfc395934a · outbound
This paper cites Sic-mmab: Synchronisation involves communi- cation in multiplayer multi-armed bandits.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Sic-mmab: Synchronisation involves communi- cation in multiplayer multi-armed bandits
Reference 2021
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.854327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a34af3d0-ca81-4a36-9627-b9c04d7eb125 · outbound
This paper cites Gambling in a rigged casino: The adversarial multi-armed bandit problem.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Gambling in a rigged casino: The adversarial multi-armed bandit problem
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.926264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cc8474a5-2653-49c6-9c2c-a885495b03b1 · outbound
This paper cites Bandit processes and dy- namic allocation indices.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Bandit processes and dy- namic allocation indices
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.798230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c3dfcf2b-268f-495b-9187-afdcc8ccd723 · outbound
This paper cites Ad hoc autonomous agent teams: Collaboration without pre-coordination.
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework Ad hoc autonomous agent teams: Collaboration without pre-coordination
Reference 2024
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T19:34:32.564075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.