Paper Citation Record · LEDGER

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2507.23080.

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

pith.paper-citation-record.v1
2507.23080 v1

Coverage vector

measured 41 of 41 reference resolution

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measured 41 of 41 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation ad457e09-c5a4-440e-b6ff-efff7afd454d · outbound

This paper cites Graph neural networks and reinforcement learning: A survey,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Graph neural networks and reinforcement learning: A survey,

Reference 1

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This paper cites Graph Attention Networks.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Graph Attention Networks

Reference 3

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Observation d63e07c8-7ad5-4fc6-a198-f0b054bbd65f · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 4

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This paper cites Exploring Causal Learning through Graph Neural Networks: An In-depth Review.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Exploring Causal Learning through Graph Neural Networks: An In-depth Review

Reference 5

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Observation ccd58124-d35e-40b0-95c7-b4b2b9b6af11 · outbound

This paper cites When graph neural network meets causality: Opportunities, methodologies and an outlook,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning When graph neural network meets causality: Opportunities, methodologies and an outlook,

Reference 6

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Observation b3e0e376-8afd-4175-a93c-d226c41af4aa · outbound

This paper cites A Survey on Causal Reinforcement Learning.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning A Survey on Causal Reinforcement Learning

Reference 7

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Observation f51342fe-2911-43e7-b070-95d6b9ba6313 · outbound

This paper cites Causal reinforcement learning: A survey,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Causal reinforcement learning: A survey,

Reference 8

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Observation 7284a51e-0154-458b-b601-6095577422c3 · outbound

This paper cites Causal Multi-Agent Reinforcement Learning: Review and Open Problems.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Causal Multi-Agent Reinforcement Learning: Review and Open Problems

Reference 9

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Observation 0d89bd45-5a7c-4e1f-b1b1-deb6a49edde9 · outbound

This paper cites Variational Graph Auto-Encoders.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Variational Graph Auto-Encoders

Reference 10

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Observation 80f512bc-2b8b-4a60-a1f6-9f55b64704ca · outbound

This paper cites Challenges and opportunities in deep reinforcement learning with graph neural networks: A comprehensive review of algorithms and applications,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Challenges and opportunities in deep reinforcement learning with graph neural networks: A comprehensive review of algorithms and applications,

Reference 11

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Observation 35286224-a290-4b1d-9131-54cd363e9fc2 · outbound

This paper cites Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments

Reference 12

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Observation 43622470-8e60-453d-8e64-1d2109eedfcb · outbound

This paper cites Generalized single-vehicle- based graph reinforcement learning for decision-making in autonomous driving,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Generalized single-vehicle- based graph reinforcement learning for decision-making in autonomous driving,

Reference 13

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Observation cfed2446-e679-49f3-873a-80ceb7336051 · outbound

This paper cites Multi-agent decision-making modes in uncertain interactive traffic scenarios via graph convolution-based deep reinforcement learning,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Multi-agent decision-making modes in uncertain interactive traffic scenarios via graph convolution-based deep reinforcement learning,

Reference 14

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Observation 3549bbb8-6cc8-46e4-8b50-deeb3605e55a · outbound

This paper cites Graph neural network and reinforcement learning for multi-agent cooperative control of con- nected autonomous vehicles,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Graph neural network and reinforcement learning for multi-agent cooperative control of con- nected autonomous vehicles,

Reference 15

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Observation bc3471ab-e7d6-46de-ba7f-a583e0eeb755 · outbound

This paper cites Cooperative Behavior Planning for Automated Driving using Graph Neural Networks.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Cooperative Behavior Planning for Automated Driving using Graph Neural Networks

Reference 16

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Observation 7fc1afc7-6a91-4024-977a-ff7eb60d4db2 · outbound

This paper cites Efficient connected and automated driving system with multi-agent graph rein- forcement learning,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Efficient connected and automated driving system with multi-agent graph rein- forcement learning,

Reference 17

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Observation 6d3093bf-9ea3-469c-a872-15bc405d0858 · outbound

This paper cites Dq-gat: Towards safe and efficient autonomous driving with deep q-learning and graph attention networks,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Dq-gat: Towards safe and efficient autonomous driving with deep q-learning and graph attention networks,

Reference 18

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Observation 290b616a-9ab9-49c5-be34-de4de1adc91e · outbound

This paper cites Drl-gat-sa: Deep reinforcement learning for autonomous driving planning based on graph attention networks and simplex architecture,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Drl-gat-sa: Deep reinforcement learning for autonomous driving planning based on graph attention networks and simplex architecture,

Reference 19

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Observation 36d9d36b-1d62-4bb8-bbc5-57a60aa3a2c6 · outbound

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Causal based q-learning,

Reference 20

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This paper cites Efficient reinforcement learning with prior causal knowledge,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Efficient reinforcement learning with prior causal knowledge,

Reference 21

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Observation 13b510a5-f631-41f2-9b14-236d281eebbf · outbound

This paper cites Counterfactual policy evaluation for decision- making in autonomous driving,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Counterfactual policy evaluation for decision- making in autonomous driving,

Reference 22

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Observation baca878d-f849-4dda-8117-6e986dec2079 · outbound

This paper cites Causality-driven Hierarchical Structure Discovery for Reinforcement Learning.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Causality-driven Hierarchical Structure Discovery for Reinforcement Learning

Reference 23

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This paper cites Constructing bayesian network models of gene expression networks from microarray data,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Constructing bayesian network models of gene expression networks from microarray data,

Reference 24

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This paper cites Multi-Channel Causal Variational Autoencoder,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Multi-Channel Causal Variational Autoencoder,

Reference 25

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Observation 1d5dc35c-3dba-4e7d-a357-8374ed87c23a · outbound

This paper cites On causally disen- tangled representations,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning On causally disen- tangled representations,

Reference 26

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Observation 8c4bd703-3c83-498d-aa8e-c36d74d10be8 · outbound

This paper cites Weakly supervised disentangled generative causal representation learning,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Weakly supervised disentangled generative causal representation learning,

Reference 27

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Observation 16dff7c4-45a7-4547-8558-dd44ab5f53b0 · outbound

This paper cites Causal- vae: Disentangled representation learning via neural structural causal models,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Causal- vae: Disentangled representation learning via neural structural causal models,

Reference 28

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Observation 99cde973-fd9c-4893-8929-b3448ea134b7 · outbound

This paper cites Concept-free Causal Disentanglement with Variational Graph Auto-Encoder.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Concept-free Causal Disentanglement with Variational Graph Auto-Encoder

Reference 29

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Cadet: A causal dis- entanglement approach for robust trajectory prediction in autonomous driving,

Reference 30

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Observation 1ff5fb6f-6ae7-48fd-a4b8-ed02b567d766 · outbound

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning How Attentive are Graph Attention Networks?

Reference 31

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Dueling network architectures for deep reinforcement learning,

Reference 32

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Information flows in causal networks,

Reference 33

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Ci-gnn: A granger causality-inspired graph neural network for interpretable brain network-based psychiatric diagnosis,

Reference 34

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This paper cites Orphicx: A causality-inspired latent variable model for interpreting graph neural networks,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Orphicx: A causality-inspired latent variable model for interpreting graph neural networks,

Reference 35

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This paper cites Estimation of renyi entropy and mutual information based on generalized nearest-neighbor graphs,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Estimation of renyi entropy and mutual information based on generalized nearest-neighbor graphs,

Reference 36

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning MINE: Mutual Information Neural Estimation

Reference 37

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Measures of entropy from data using infinitely divisible kernels,

Reference 38

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This paper cites An environment for autonomous driving decision-making,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning An environment for autonomous driving decision-making,

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Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Congested traffic states in empirical observations and microscopic simulations,

Reference 40

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This paper cites Reasoning graph-based reinforce- ment learning to cooperate mixed connected and autonomous traffic at unsignalized intersections,.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Reasoning graph-based reinforce- ment learning to cooperate mixed connected and autonomous traffic at unsignalized intersections,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:11:23.910678Z

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This paper cites Available: https://doi.org/10.1016/j.sysarc.2022.102505.

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning Available: https://doi.org/10.1016/j.sysarc.2022.102505

Reference 2022

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