Pith. sign in

Paper Citation Record · LEDGER

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning

As of 12 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2501.10938.

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

pith.paper-citation-record.v1
2501.10938 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:54:19.227490Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

53 of 53 outbound references displayed

  • verified exact1
  • verified fuzzy40
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b36eabe-b713-473a-b152-9f742ef26701 · outbound

This paper cites A reinforcement learning method for human-robot collaboration in assembly tasks,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning A reinforcement learning method for human-robot collaboration in assembly tasks,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:20.094013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:18.975964Z digest=sha256:b9b8cacecd9fb21cb515a7f708891954572140fd3e2dbdba03e209879ff94452

Observation 04fed452-9fe5-4dad-94f0-a0f2c4ca2c5e · outbound

This paper cites IoT sensor selection for target localization: A reinforcement learning based approach,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning IoT sensor selection for target localization: A reinforcement learning based approach,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:20.078359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:18.981313Z digest=sha256:9c34da36b8a45a1966591e3e38e2654653cb6caa4e26644c9aff9ce305f2d030

Observation f8d50044-7601-4622-aa79-c0bc0c864ca1 · outbound

This paper cites Self- supervised online and light-weight anomaly and event detection for iot devices,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Self- supervised online and light-weight anomaly and event detection for iot devices,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:20.062564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:18.986492Z digest=sha256:8a3700c14e08ef31497b8f48808b55d8d61a918967587e8acb451455bacc079f

Observation e1761ab0-e548-4a9a-a317-ffc6a7f8f1c5 · outbound

This paper cites Mastering the game of go without human knowledge,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Mastering the game of go without human knowledge,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:18.991666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:18.991666Z digest=sha256:297b5df7a453a326a588fdc6c880a91a7e97670d6038be2b1fabe942e5e74253

Observation 713fb8e3-3f70-4bf2-b1b8-f6436955e3a9 · outbound

This paper cites Dota 2 with Large Scale Deep Reinforcement Learning.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Dota 2 with Large Scale Deep Reinforcement Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:18.997231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:18.997231Z digest=sha256:6eb7837cd2562bb65238e533f256b9d2d6265aafdce1070907413b8b411c81c1

Observation 4f40ba40-dca8-41b5-a0ac-01049c1bd02a · outbound

This paper cites Multi-agent deep reinforcement learning to manage connected autonomous vehicles at tomorrow’s inter- sections,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Multi-agent deep reinforcement learning to manage connected autonomous vehicles at tomorrow’s inter- sections,

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.002789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.002789Z digest=sha256:0b7e7b1c6353f5a6b9b4af4297bd1c498903146603ff36da0c461f8f55af2c1f

Observation 9f1b34a7-47c5-42e7-9aaa-47c1c1496ed4 · outbound

This paper cites Target lo- calization using multi-agent deep reinforcement learning with proximal policy optimization,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Target lo- calization using multi-agent deep reinforcement learning with proximal policy optimization,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.008107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.008107Z digest=sha256:e1108cdf8170beda166d147a0256eed082d0010cdb09f0c35416af224b4582c5

Observation b9929436-c00a-4b71-9e0e-eebf61745336 · outbound

This paper cites Fault- tolerant federated reinforcement learning with theoretical guarantee,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Fault- tolerant federated reinforcement learning with theoretical guarantee,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:20.016473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.012763Z digest=sha256:6d7429f6aff7e4c91d0a2a56eff12c5a45a586579a7dde33fb67978cb88ea394

Observation bee9843b-de19-4629-bfa3-14220e450d86 · outbound

This paper cites Resource allocation in iot edge computing via concurrent federated reinforcement learning,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Resource allocation in iot edge computing via concurrent federated reinforcement learning,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.999842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.017471Z digest=sha256:097a278957360269827fecdbc2f819b2a30ad02c43ee881319f8d0b83cb8ad18

Observation 1c3d613e-ffa2-4084-b849-03d26e0fd8bb · outbound

This paper cites Federated reinforcement learn- ing for fast personalization,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Federated reinforcement learn- ing for fast personalization,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.982037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.022139Z digest=sha256:204e14dcb3d937a62056330e626e6f0d70a860e15c107c00543b5783f4bd9c22

Observation 5f636dd2-1368-46e4-8a63-a2302e8f6942 · outbound

This paper cites Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.965846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.027684Z digest=sha256:ce5c70aa6ae6faec807b5715837ef89d1aec2ef46bf0ed530e76eb03636e7208

Observation 9f09f157-6264-44c4-b2c0-d4272e4a8f12 · outbound

This paper cites Learning to utilize shaping rewards: A new approach of reward shaping,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Learning to utilize shaping rewards: A new approach of reward shaping,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.948821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.032289Z digest=sha256:9daca81da7098cf698234d07d1d839ca22d43b014e9f92aa9a263425e73592b2

Observation abcf40a3-55e0-45a8-ae1d-8d96b4a48e39 · outbound

This paper cites Graph convolutional recurrent networks for reward shaping in reinforcement learning,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Graph convolutional recurrent networks for reward shaping in reinforcement learning,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.932315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.037706Z digest=sha256:dc5887488b92d0727026e6bb5b0bcfae8f2b6c93b054c6f61ba95516f16f6c7a

Observation 0dacecef-2c40-46aa-9e6f-94008007921d · outbound

This paper cites Reward Shaping Using Convolutional Neural Network.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Reward Shaping Using Convolutional Neural Network

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:54:19.341068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.042501Z digest=sha256:9de410040bb90082ebcd933f854671d18657dd504117348978b57d10c05d06c0

Observation 87332c17-9d06-4394-ac23-fdb50d036692 · outbound

This paper cites Federated learning for internet of things: A comprehensive survey,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Federated learning for internet of things: A comprehensive survey,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.915409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.047831Z digest=sha256:564ce2a3fbcf7eddbf1b27cc854575965d236a9a09b176bd3cd0e03da67e0b65

Observation 6cee09f1-8dd1-4a7b-afc3-80657def30f2 · outbound

This paper cites Knowledge distillation: A survey,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Knowledge distillation: A survey,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.053345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.053345Z digest=sha256:d9668dcd6594cc5cb75caf2e9599703a93701c4e79834c3e8082e5b9fcbc49fb

Observation 2e3eef1e-6bd8-49b4-add6-b890f1b7c7b4 · outbound

This paper cites Federated Reinforcement Learning: Techniques, Applications, and Open Challenges.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Federated Reinforcement Learning: Techniques, Applications, and Open Challenges

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.058241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.058241Z digest=sha256:ace86c6697dbe8db3875c798a2be80670ce3b955c554a5c9ed229e5dc449b381

Observation 2e819415-e1df-4440-ac19-07042cd00a5d · outbound

This paper cites Overcoming exploration in reinforcement learning with demonstrations,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Overcoming exploration in reinforcement learning with demonstrations,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.889012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.063277Z digest=sha256:59f91b05219a4f75cc85e4e397d613eabae8453fceb7cab3aec11aca391c0aec

Observation 49ffafec-7dd3-4c35-9776-5e0d80eaf403 · outbound

This paper cites Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.067832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.067832Z digest=sha256:5c6c60ccaef5d933fd4551029af7523828b4a07df4c8b7b62324b73fbd27c6e3

Observation 75b54225-ec3d-46e0-9e0f-5d7eeafecbf6 · outbound

This paper cites Federated learning meets blockchain in edge computing: Opportunities and challenges,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Federated learning meets blockchain in edge computing: Opportunities and challenges,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.072667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.072667Z digest=sha256:df6bab75d5d62b13e0ba08eacc18d3f20cceeb7bd0e0656f014179ebb746bb63

Observation 64cc76fc-eb81-4d71-9092-47e6931f6960 · outbound

This paper cites A context-aware blockchain-based crowdsourcing framework: Open challenges and op- portunities,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning A context-aware blockchain-based crowdsourcing framework: Open challenges and op- portunities,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.861715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.077521Z digest=sha256:e58e360051222932a86e7bc9219416f84a3581077c79f7e1bb43ce2b8b3c5afa

Observation 89093bfd-5ab0-4232-b90a-2bb2cdfb7240 · outbound

This paper cites Federated multiagent actor– critic learning for age sensitive mobile-edge computing,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Federated multiagent actor– critic learning for age sensitive mobile-edge computing,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.845145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.082304Z digest=sha256:f4d5ef97f3ddef9d9681ec849c3d12d33afc642de7cf64316e87432523cb032b

Observation 721ced6c-738d-40fd-a907-d40473d8754c · outbound

This paper cites In-edge ai: Intelligentizing mobile edge computing, caching and communication by federated learning,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning In-edge ai: Intelligentizing mobile edge computing, caching and communication by federated learning,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.087158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.087158Z digest=sha256:1be56b861d39d1b32782a63a821a27cf6b7bb148ee19e6beb16cf9af06417cd3

Observation 84603e51-9e1d-451a-883e-0051d11be0f0 · outbound

This paper cites When deep rein- forcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5g ultradense network,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning When deep rein- forcement learning meets federated learning: Intelligent multitimescale resource management for multiaccess edge computing in 5g ultradense network,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.815015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.091648Z digest=sha256:32f7e81a1861335d3ccc0ed203f8611b145f3665805bc477ae0c4b7067f974d5

Observation 333c33f0-e8be-4544-a456-6170a51ef34f · outbound

This paper cites Lifelong federated reinforcement learn- ing: a learning architecture for navigation in cloud robotic systems,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Lifelong federated reinforcement learn- ing: a learning architecture for navigation in cloud robotic systems,

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.096204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.096204Z digest=sha256:abda6297e9e7489c5d2a8275fcabf7d9b4d6db7c2837f809996748cfa645477a

Observation 01bae6c8-747f-4b10-a295-7b787fe6a43a · outbound

This paper cites Federated transfer reinforcement learning for autonomous driving,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Federated transfer reinforcement learning for autonomous driving,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.785513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.100611Z digest=sha256:a156dd503fa588e99e50106e556a9dda01c9191f32ac2d3d603049dae4c425bb

Observation 5f9261eb-37b4-4adc-8709-4997df232c40 · outbound

This paper cites Double Q-learning for radiation source detection,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Double Q-learning for radiation source detection,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.769754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.105106Z digest=sha256:2dd5599e7fbc0735f1c1c31451349ed56bb333d0848efd75e56c10a1938b13de

Observation a57a4cdc-d343-48e2-98e7-ce220606d3e4 · outbound

This paper cites Multi- agent deep reinforcement learning with demonstration cloning for target localization,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Multi- agent deep reinforcement learning with demonstration cloning for target localization,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.753153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.109500Z digest=sha256:ffb3eaed958b656fce4124c75dca34d1c780184ea43b9cf6310e00b2cbdfaf18

Observation 106687d1-a1a6-48e3-b236-76bf925afb16 · outbound

This paper cites Emergent tool use from multi-agent autocurricula,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Emergent tool use from multi-agent autocurricula,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.737171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.114251Z digest=sha256:3bee27d1f88fc1a2627eed234198c141b1ef997bbd0ffdaeeb7f5b5aed4a06ce

Observation ad1434d7-786b-4588-bd38-cc1b79844032 · outbound

This paper cites Principled reward shaping for rein- forcement learning via lyapunov stability theory,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Principled reward shaping for rein- forcement learning via lyapunov stability theory,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.721438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.119798Z digest=sha256:14a4597f7e428161295201bfcbc5e265bd4cfadc71cb639fae5356a86ef88b6d

Observation 9f12947d-118e-4b60-8314-400a3dccea29 · outbound

This paper cites Primal: Pathfinding via reinforcement and imitation multi- agent learning,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Primal: Pathfinding via reinforcement and imitation multi- agent learning,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.705047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.124284Z digest=sha256:8766711fd16a3b409c91150dd22bbe4b0400aa8f3fbe066f152a574fd3834389

Observation 17214677-742f-45fb-a36b-97c2d5d9b664 · outbound

This paper cites Primal 2: Pathfind- ing via reinforcement and imitation multi-agent learning-lifelong,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Primal 2: Pathfind- ing via reinforcement and imitation multi-agent learning-lifelong,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.688654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.128770Z digest=sha256:fae54a9ea16bf5d66ba2485644e8f97c9c333669e1eb1decd41f0a7663fd35c4

Observation bf3725d7-bf9a-4a3a-8ed2-a6e2c2a03077 · outbound

This paper cites Multi-agent deep reinforcement learning: a survey,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Multi-agent deep reinforcement learning: a survey,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.667066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.133139Z digest=sha256:0f08b1add73ce2041a3eda16c2b71c6308f39d75d05145fdcb0e06d8eaf71713

Observation 8fb34b76-d77f-4721-89c3-69fa944ab3c7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.137689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.137689Z digest=sha256:d15d298c18f776659387a28f6cd4ece57c3c37b76941fded9bd394fff112bc6e

Observation 6afa10c5-0bca-47bc-abc2-05b9aa6e7d47 · outbound

This paper cites High- dimensional continuous control using generalized advantage estimation,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning High- dimensional continuous control using generalized advantage estimation,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.650794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.142508Z digest=sha256:17e8b501cb412fc200e1f5ea0517373ad6b7fa586559e478fe1fc43c53d3c212

Observation 203277c9-6b80-4c61-8689-633d8481f284 · outbound

This paper cites Roulette-wheel selection via stochastic acceptance,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Roulette-wheel selection via stochastic acceptance,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.634122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.147059Z digest=sha256:578efde9fc9a70c2d096c63690b3cb10228db2ad3f26b9d1b94958ae41015c11

Observation a0e0f091-cc78-46fa-95dc-93724b49187d · outbound

This paper cites Influence-and interest- based worker recruitment in crowdsourcing using online social net- works,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Influence-and interest- based worker recruitment in crowdsourcing using online social net- works,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.619133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.151682Z digest=sha256:ca192e31d02d15c7bf6cce910a48774904508c4e859e725d7c8ce01aab1ab23b

Observation 7ef7c5fe-5936-4faa-9999-a6c98522c20c · outbound

This paper cites On- chain behavior prediction machine learning model for blockchain-based 14 crowdsourcing,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning On- chain behavior prediction machine learning model for blockchain-based 14 crowdsourcing,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.603783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.156708Z digest=sha256:a2a9b47a918b20543fcf3d1735b6290a89533276f5981daa8ea2423215c0109d

Observation 25a3a1ec-5c9b-4d84-ace9-077da33274b5 · outbound

This paper cites IPFS - Content Addressed, Versioned, P2P File System.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning IPFS - Content Addressed, Versioned, P2P File System

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T18:54:19.161376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:54:19.161376Z digest=sha256:67d5bc0eb2c1f2f5e89af40f20aac71203d8f8df51c3cb4a0b806eb966f9f36f

Observation 3dac2287-c7b9-48ba-b0a5-2ae5018f6a58 · outbound

This paper cites An optimization and auction-based incentive mechanism to maximize social welfare for mobile crowdsourcing,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning An optimization and auction-based incentive mechanism to maximize social welfare for mobile crowdsourcing,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.587956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.166316Z digest=sha256:2c0a084eb301b3faa2d20289f4f1bb6c0a4b11a4bf4a22902cd72b196a75a96e

Observation dcf82a82-0968-4408-89b4-951a9d354ad9 · outbound

This paper cites A worker-selection incentive mechanism for optimizing platform-centric mobile crowdsourcing sys- tems,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning A worker-selection incentive mechanism for optimizing platform-centric mobile crowdsourcing sys- tems,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.572389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.170880Z digest=sha256:056a412808ce42061475ec53e569b8e68990e2b44d21d3f21fb646c1025c0624

Observation 8d1aadb1-45c7-4140-85cb-98bc59c70dff · outbound

This paper cites Auction fever: Rising revenue in second-price auction formats,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Auction fever: Rising revenue in second-price auction formats,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.556907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.175427Z digest=sha256:621ad23c97940aafb213bf811b218b3c30aeb0cafc34ffd92d17e3e60e77f289

Observation baf3eb19-fa66-4c0e-b766-c0477e1e65e4 · outbound

This paper cites Path planning and scheduling for a fleet of autonomous vehicles,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Path planning and scheduling for a fleet of autonomous vehicles,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.541367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.180100Z digest=sha256:2a3b178b45e5a8cd0f0d7dc9db306ed5e712f5dbc54357e2f71773849e41612b

Observation d36e07c8-173e-4559-b7e0-245ae5563799 · outbound

This paper cites Autonomous vehicle fleet coordination with deep reinforce- ment learning,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Autonomous vehicle fleet coordination with deep reinforce- ment learning,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.524954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.184827Z digest=sha256:a334bfacbde246043c2d49dfe92157d58ca2416fa52bd307a9fb38b2f1ad5009

Observation e7411301-cd24-4f55-8dff-89f4059d99f7 · outbound

This paper cites Multi-agent reinforcement learning with di- rected exploration and selective memory reuse,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Multi-agent reinforcement learning with di- rected exploration and selective memory reuse,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.508189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.189811Z digest=sha256:624326a4aa447daf854479c405c88220accea748b3471bd31e38d26fe6b9acbf

Observation 54bc74fb-09dc-4983-ba4b-b025b353f818 · outbound

This paper cites Data-driven dynamic active node selection for event localization in IoT applications-a case study of radiation localization,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Data-driven dynamic active node selection for event localization in IoT applications-a case study of radiation localization,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.492301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.194537Z digest=sha256:4ff2fb2de88044f8f2e67dbb76fd7b42bd6f2cb1991c1e67aaf1d2c16da6a7be

Observation 6169b1ea-8a36-41dc-bac5-1a1d70eb9666 · outbound

This paper cites Reinforcement learn- ing framework for uav-based target localization applications,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Reinforcement learn- ing framework for uav-based target localization applications,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.476036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.199215Z digest=sha256:a9092806699d6516f1618a5ec21eb8d613d0fdd2b3cc5bf5a533e959450bce3f

Observation 154a7028-4964-4d4e-b027-b3e51978723b · outbound

This paper cites A predictive target tracking framework for iot using cnn–lstm,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning A predictive target tracking framework for iot using cnn–lstm,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.459449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.204055Z digest=sha256:cadf48566f27c353e2911abec794ac5ecd98b3b167ce0db099a96ed8524f2072

Observation fe7d37f9-527a-4b16-acfc-20f125bc31ff · outbound

This paper cites RFLS-resilient fault- proof localization system in IoT and crowd-based sensing applications,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning RFLS-resilient fault- proof localization system in IoT and crowd-based sensing applications,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.441035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.208581Z digest=sha256:0e6fe36cd92e1bad624664c0948ad585795ed65a0064c48c81acaa07c36d69ad

Observation f3954c10-3e49-4e6a-86bb-7c335cbbfb93 · outbound

This paper cites SDRS: A stable data-based recruitment system in IoT crowdsensing for localiza- tion tasks,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning SDRS: A stable data-based recruitment system in IoT crowdsensing for localiza- tion tasks,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.424868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.213049Z digest=sha256:94bd651c5a9ae841095912a36b3736cae4158666c5fc66f93e0265c26aac08ca

Observation fafdc694-aa35-45ce-b5d1-81f1ed07bd5e · outbound

This paper cites A uav- assisted search and localization strategy in non-line-of-sight scenarios,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning A uav- assisted search and localization strategy in non-line-of-sight scenarios,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.408887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.217885Z digest=sha256:1d54c258e9f5ecc3709b0d703d8f3d44aa9e3c179c517e311cb57a327711859b

Observation e3f0d804-a321-4884-a6b0-94382ca5ef84 · outbound

This paper cites A matching game-based crowdsourcing framework for last-mile delivery: Ground-vehicles and unmanned-aerial vehicles,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning A matching game-based crowdsourcing framework for last-mile delivery: Ground-vehicles and unmanned-aerial vehicles,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.392639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.222608Z digest=sha256:22297c6b3500efdaf403cd2344186f0be524c5759e24abeb5bd05fd45eaec396

Observation e665bd22-862b-4479-9081-3a6e27cc0ed0 · outbound

This paper cites Lenet-5, convolutional neural networks,.

Blockchain-assisted Demonstration Cloning for Multi-Agent Deep Reinforcement Learning Lenet-5, convolutional neural networks,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:54:19.376243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:54:19.227490Z digest=sha256:95abbf5d4508be2bf219714cc8f88fb047ed95428584c0b0b5c61cd0afb84e22

Pith citing papers

No inbound Pith citation observations are available.