Paper Citation Record · LEDGER

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control

As of 10 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 2 inbound Pith citation observations for arXiv:2502.03640.

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

pith.paper-citation-record.v1
2502.03640 v3

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:23:18.367381Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T07:54:12.950136Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T11:39:46.366290Z

Reference resolution

75 of 75 outbound references displayed

verified exact1
verified fuzzy56
unresolved18
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2cc078e8-d915-40e1-af18-f8715862a839 · outbound

This paper cites Constrained policy optimization.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Constrained policy optimization

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.699861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4f016e62-36c1-45ac-a3ff-9b5bb73cbac5 · outbound

This paper cites Safe policy synthesis in multi-agent pomdps via discrete-time barrier functions.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe policy synthesis in multi-agent pomdps via discrete-time barrier functions

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.624898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a11c6362-c6c9-409a-953a-4f19ec67724f · outbound

This paper cites Control barrier function based quadratic programs for safety critical systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Control barrier function based quadratic programs for safety critical systems

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.567100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aca1f0cb-1a8d-43ee-aa98-feea29dad1e8 · outbound

This paper cites Vmas: A vectorized multi-agent simulator for collective robot learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Vmas: A vectorized multi-agent simulator for collective robot learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.523910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c00158bf-e878-4b92-a89c-dd880df24907 · outbound

This paper cites Benchmarl: Benchmarking multi-agent reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Benchmarl: Benchmarking multi-agent reinforcement learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.488395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3fb2ad30-a226-4b79-9854-9f67902b24dc · outbound

This paper cites Powergridworld: A framework for multi-agent reinforcement learning in power systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Powergridworld: A framework for multi-agent reinforcement learning in power systems

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.467749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 285018de-6206-40a0-b79f-ca8a23429979 · outbound

This paper cites Adaptation for validation of consolidated control barrier functions.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Adaptation for validation of consolidated control barrier functions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:17.480595Z

Source-reported events for the cited work

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Observation 1522dfd5-e458-41d0-8bca-45f51ffdf4a9 · outbound

This paper cites An actor-critic algorithm for constrained markov decision processes.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control An actor-critic algorithm for constrained markov decision processes

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.423392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 53f750a4-d54e-406d-9556-2763d5de967f · outbound

This paper cites Control barrier certificates for safe swarm behavior.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Control barrier certificates for safe swarm behavior

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.348653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 83bd8c0b-8945-4bfa-bd70-341515013231 · outbound

This paper cites JAX : composable transformations of P ython+ N um P y programs, 2018.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control JAX : composable transformations of P ython+ N um P y programs, 2018

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:17.493583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfa3c861-d64b-428b-b656-7dd90ba4b2a7 · outbound

This paper cites Socially aware motion planning with deep reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Socially aware motion planning with deep reinforcement learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.221914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 41b04c53-e87f-4a79-a4c3-011e8f8f1e8e · outbound

This paper cites Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.143946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 068edb22-b691-4c6b-a9b0-43405d4ffddb · outbound

This paper cites Backup control barrier functions: Formulation and comparative study.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Backup control barrier functions: Formulation and comparative study

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.083479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1e5a5589-2e30-4a70-838e-6075dfaa7f57 · outbound

This paper cites End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.069063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b573fe3a-4b42-49ac-8cef-ac74c1fc4d10 · outbound

This paper cites Safe nonlinear control using robust neural lyapunov-barrier functions.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe nonlinear control using robust neural lyapunov-barrier functions

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.054383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e3c75784-dc10-45e5-9d78-3fea4f8fe939 · outbound

This paper cites Provably efficient generalized lagrangian policy optimization for safe multi-agent reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Provably efficient generalized lagrangian policy optimization for safe multi-agent reinforcement learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.040107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a0ae6fe7-66c1-4984-81fe-49a57dcbf61b · outbound

This paper cites Safe reinforcement learning using robust control barrier functions.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe reinforcement learning using robust control barrier functions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.018795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 41c2f504-7870-4c0f-b733-cb37a28c610b · outbound

This paper cites Motion planning among dynamic, decision-making agents with deep reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Motion planning among dynamic, decision-making agents with deep reinforcement learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:20.004001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 093ab9bb-5080-474c-8bc6-3a43a288b370 · outbound

This paper cites Iterative reachability estimation for safe reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Iterative reachability estimation for safe reinforcement learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.987462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation df234578-c92a-4c08-b9cc-550ac1850a21 · outbound

This paper cites Learning safe control for multi-robot systems: Methods, verification, and open challenges.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Learning safe control for multi-robot systems: Methods, verification, and open challenges

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.972747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 92fc3958-ec30-42df-ae5a-ce4c55506887 · outbound

This paper cites A reinforcement learning framework for vehicular network routing under peak and average constraints.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control A reinforcement learning framework for vehicular network routing under peak and average constraints

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.958294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f82ad7f7-416a-419d-b4be-932a950a1cb8 · outbound

This paper cites Nonsmooth barrier functions with applications to multi-robot systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Nonsmooth barrier functions with applications to multi-robot systems

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.942951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4645099c-3c03-4d95-987a-5b498e888e58 · outbound

This paper cites Deadlock analysis and resolution for multi-robot systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Deadlock analysis and resolution for multi-robot systems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.928493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fd7d548f-198e-4c9c-b24a-ce595e90522c · outbound

This paper cites Multi-Agent Constrained Policy Optimisation.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Multi-Agent Constrained Policy Optimisation

Reference 24

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Source-reported events for the cited work

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Observation cb57f816-9bf3-4074-b47b-4b07e2f920ac · outbound

This paper cites Safe multi-agent reinforcement learning for multi-robot control.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe multi-agent reinforcement learning for multi-robot control

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.871053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8c23643a-d174-4ddc-96b9-7f16b2a07874 · outbound

This paper cites Optimal control barrier functions for rl based safe powertrain control.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Optimal control barrier functions for rl based safe powertrain control

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.823970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f151f7fd-2b9a-44ce-b52c-d4800adcff93 · outbound

This paper cites Autocost: Evolving intrinsic cost for zero-violation reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Autocost: Evolving intrinsic cost for zero-violation reinforcement learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.742433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 87db835f-cea4-42f0-aeaa-791d51165616 · outbound

This paper cites The safety filter: A unified view of safety-critical control in autonomous systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control The safety filter: A unified view of safety-critical control in autonomous systems

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.686209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8cf75d24-5ae6-4924-8d57-f8c8ea4946e7 · outbound

This paper cites Safedreamer: Safe reinforcement learning with world models.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safedreamer: Safe reinforcement learning with world models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.663782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8cc67af3-80ea-4d92-bf2a-69a3f4e7a08e · outbound

This paper cites Multiagent systems with cbf-based controllers: Collision avoidance and liveness from instability.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Multiagent systems with cbf-based controllers: Collision avoidance and liveness from instability

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.647224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d7c7f46e-c451-4c20-b667-9e238cf0f88b · outbound

This paper cites Distributed optimization in multi-agent robotics for industry 4.0 warehouses.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Distributed optimization in multi-agent robotics for industry 4.0 warehouses

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.630155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0e3f7cd9-ae6b-4c47-b957-d2a136306b1a · outbound

This paper cites Lidar-based online control barrier function synthesis for safe navigation in unknown environments.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Lidar-based online control barrier function synthesis for safe navigation in unknown environments

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.614155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3e77e332-bd45-4ad6-8698-df4474d622c2 · outbound

This paper cites Rpcbf: Constructing safety filters robust to model error and disturbances via policy control barrier functions.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Rpcbf: Constructing safety filters robust to model error and disturbances via policy control barrier functions

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.591635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9354c862-493b-4828-b38d-6eb57d90e271 · outbound

This paper cites Control barrier functions for multi-agent systems under conflicting local signal temporal logic tasks.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Control barrier functions for multi-agent systems under conflicting local signal temporal logic tasks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.575997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1060432d-1866-4ed3-9749-9011ad616aae · outbound

This paper cites Learning hybrid control barrier functions from data.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Learning hybrid control barrier functions from data

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.559959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2f5ac665-f31c-4e04-9305-abf013f7c317 · outbound

This paper cites Conflict-averse gradient descent for multi-task learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Conflict-averse gradient descent for multi-task learning

Reference 36

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Source-reported events for the cited work

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Observation af5f4e69-d5a5-4828-b3a6-3f3cc5ba9db4 · outbound

This paper cites Cmix: Deep multi-agent reinforcement learning with peak and average constraints.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Cmix: Deep multi-agent reinforcement learning with peak and average constraints

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.529279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46b6f97e-aef1-4e92-a213-55b5e24cd418 · outbound

This paper cites Towards optimally decentralized multi-robot collision avoidance via deep reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Towards optimally decentralized multi-robot collision avoidance via deep reinforcement learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.512433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4cddd333-8118-4ff7-a02d-b52466981258 · outbound

This paper cites Decentralized policy gradient descent ascent for safe multi-agent reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Decentralized policy gradient descent ascent for safe multi-agent reinforcement learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.497292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7d08c408-8c4e-4506-ba47-5acdeb176efb · outbound

This paper cites Safe value functions.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe value functions

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.482295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0d044241-4877-413b-96f6-bd29134783ca · outbound

This paper cites Scalable multi-agent reinforcement learning through intelligent information aggregation.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Scalable multi-agent reinforcement learning through intelligent information aggregation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.450639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c729bdbd-f12b-4fea-8a2b-ffb132f54994 · outbound

This paper cites Safe optimal control using stochastic barrier functions and deep forward-backward sdes.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe optimal control using stochastic barrier functions and deep forward-backward sdes

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.399934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0603f6dd-6c64-491f-a091-951f90fb42c7 · outbound

This paper cites Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Decentralized Safe Multi-agent Stochastic Optimal Control using Deep FBSDEs and ADMM

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:17.948825Z

Source-reported events for the cited work

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Observation b057cc20-68ff-4206-a889-a2bb2f3886fd · outbound

This paper cites Automated and formal synthesis of neural barrier certificates for dynamical models.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Automated and formal synthesis of neural barrier certificates for dynamical models

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.356020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4dfdbf4a-3279-4b65-bd99-803bfcfda8d0 · outbound

This paper cites Learning safe multi-agent control with decentralized neural barrier certificates.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Learning safe multi-agent control with decentralized neural barrier certificates

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.306972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89c4adf4-8b27-495d-91c9-46fc7ee7f625 · outbound

This paper cites Control barrier function-based quadratic programs introduce undesirable asymptotically stable equilibria.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Control barrier function-based quadratic programs introduce undesirable asymptotically stable equilibria

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.277010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b37a104b-8d52-4b3e-9852-b6aa043cb2c7 · outbound

This paper cites Learning barrier functions for constrained motion planning with dynamical systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Learning barrier functions for constrained motion planning with dynamical systems

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.262119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d39ac098-24a1-42bc-b69c-9faa48d10e42 · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:17.972454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 972e8e28-d872-4245-bd22-41f8422aa3b8 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Proximal Policy Optimization Algorithms

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:17.977154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 322cb5cd-f641-4e8b-9d7c-3847fb10853f · outbound

This paper cites Multi-agent motion planning for dense and dynamic environments via deep reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Multi-agent motion planning for dense and dynamic environments via deep reinforcement learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.247767Z

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Observation 8d37c98d-c18f-4a2c-94e7-ae8fbd49e299 · outbound

This paper cites Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:17.986192Z

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Observation 830c9e5b-4cf8-4003-8a09-f55652b97ced · outbound

This paper cites Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:17.993477Z

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Observation 2cf34fcf-43a3-488f-b145-ca1f88dc5ffc · outbound

This paper cites Solving stabilize-avoid optimal control via epigraph form and deep reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Solving stabilize-avoid optimal control via epigraph form and deep reinforcement learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.231689Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ea7f451e-6dc2-4d7f-a4b7-1195900569fd · outbound

This paper cites How to train your neural control barrier function: Learning safety filters for complex input-constrained systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control How to train your neural control barrier function: Learning safety filters for complex input-constrained systems

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.215093Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2d23b72a-c66d-4e57-a1bb-12ad01834c8e · outbound

This paper cites Synthesis of control barrier functions using a supervised machine learning approach.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Synthesis of control barrier functions using a supervised machine learning approach

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.199997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 034516ae-6b8e-464e-bb25-dbdff9927958 · outbound

This paper cites A predictive safety filter for learning-based racing control.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control A predictive safety filter for learning-based racing control

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.183241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 77fef43e-2499-477c-a101-c012a2b2cc2a · outbound

This paper cites Mankowitz, and Shie Mannor.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Mankowitz, and Shie Mannor

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.168023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2ae3cc51-6277-4eed-8a7a-7a74afea322c · outbound

This paper cites Mujoco: A physics engine for model-based control.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Mujoco: A physics engine for model-based control

Reference 58

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-09T04:23:18.519675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 62a57698-73f7-4ad4-b7ab-3d984deece88 · outbound

This paper cites Graph Attention Networks.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Graph Attention Networks

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.215614Z

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Observation b93f13af-a490-4659-9b0d-f75bf0a2af9e · outbound

This paper cites Safety barrier certificates for collisions-free multirobot systems.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safety barrier certificates for collisions-free multirobot systems

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.152643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3f13743c-4d69-4a6e-9a2c-23a74b972dbf · outbound

This paper cites Simple statistical gradient-following algorithms for connectionist reinforcement learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Simple statistical gradient-following algorithms for connectionist reinforcement learning

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.271512Z

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Observation 38c6653a-5eca-4f57-9bbd-5c589f79828d · outbound

This paper cites Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.099706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8e744289-683f-461a-b649-982373a12533 · outbound

This paper cites Control barrier functions for systems with high relative degree.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Control barrier functions for systems with high relative degree

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:19.013924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 414f204f-f8a7-47cd-b7e6-94fb8ad3ac81 · outbound

This paper cites Crpo: A new approach for safe reinforcement learning with convergence guarantee.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Crpo: A new approach for safe reinforcement learning with convergence guarantee

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:18.901626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a4693d90-71ed-4ecc-9d43-cd70e49af526 · outbound

This paper cites Robustness of control barrier functions for safety critical control.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Robustness of control barrier functions for safety critical control

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:18.821221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 31dd5472-38dc-4e8c-ad51-b5ace86ab01b · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control The surprising effectiveness of ppo in cooperative multi-agent games

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.303990Z

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Observation 3be038ca-5b30-4f0f-b1ad-2413f5abf639 · outbound

This paper cites Gradient surgery for multi-task learning.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Gradient surgery for multi-task learning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.315009Z

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Observation 8601e4bd-f835-4046-9480-d4831b5cda6c · outbound

This paper cites Safe reinforcement learning using robust mpc.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Safe reinforcement learning using robust mpc

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:18.784474Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8dd43b2c-c068-4e3f-92e3-0e5d1ed2a57d · outbound

This paper cites Neural graph control barrier functions guided distributed collision-avoidance multi-agent control.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Neural graph control barrier functions guided distributed collision-avoidance multi-agent control

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:18.769389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9e2a26ed-506a-4c98-ae88-a0d7a075f8f9 · outbound

This paper cites Gcbf+: A neural graph control barrier function framework for distributed safe multi-agent control.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Gcbf+: A neural graph control barrier function framework for distributed safe multi-agent control

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.337230Z

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Observation d564a09d-3715-4af9-a53f-bea26746719c · outbound

This paper cites Multi-agent first order constrained optimization in policy space.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Multi-agent first order constrained optimization in policy space

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T04:23:18.745624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5a4a9d2a-8a52-485e-a3f7-cafe664722ab · outbound

This paper cites Decentralized Safe and Scalable Multi-Agent Control under Limited Actuation.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Decentralized Safe and Scalable Multi-Agent Control under Limited Actuation

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.352468Z

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Observation 88b7418d-0667-424b-9b44-16d4a416d19c · outbound

This paper cites @esa (Ref.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control @esa (Ref

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.357689Z

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Unavailable: canonical work link unavailable.

Observation 37a802bb-6860-45bd-9bdc-57a620df330f · outbound

This paper cites an unresolved cited work.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Unresolved cited work

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.362767Z

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Unavailable: canonical work link unavailable.

Observation 7a34f227-91c3-4b23-8ca3-01a0e49b76db · outbound

This paper cites an unresolved cited work.

Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control Unresolved cited work

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-09T04:23:18.367381Z

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Pith citing papers

Observation f19839a0-4bd1-45a2-8b15-b24525f0c226 · inbound

How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models? cites this paper.

How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models? Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:57:33.074108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 97f9ceb7-ed04-4385-a7cc-b3fc995e0024 · inbound

Safe and Generalizable Hierarchical Multi-Agent RL via Constraint Manifold Control cites this paper.

Safe and Generalizable Hierarchical Multi-Agent RL via Constraint Manifold Control Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-04T11:39:46.367847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.