Pith. sign in

Paper Citation Record · LEDGER

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning

As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2412.02570.

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

pith.paper-citation-record.v1
2412.02570 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:23:35.238983Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:12:51.061553Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T20:12:51.206980Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact2
  • verified fuzzy45
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 844f4274-6458-4841-967e-b9e29b1367fe · outbound

This paper cites Exploration and apprenticeship learning in reinforcement learning.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Exploration and apprenticeship learning in reinforcement learning

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:37.233805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.180857Z digest=sha256:21f5495d2111e303dfb0f3eb500c5fc09d3e3c86734f428d8ca9918c6761b640

Observation 4bedadb3-a418-4956-bfde-30bb0bc4bc38 · outbound

This paper cites Adversarial deep reinforcement learning to mitigate sensor and communication attacks for secure swarm robotics.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Adversarial deep reinforcement learning to mitigate sensor and communication attacks for secure swarm robotics

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:37.225169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.184247Z digest=sha256:350bcbc3f57589dd11f536be4ab5c9fb2871e6da5d23c40570620345026f118b

Observation b7206927-fc79-4f0e-a28e-cb49ac707c46 · outbound

This paper cites A survey of inverse reinforcement learning.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning A survey of inverse reinforcement learning

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:37.215799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.186705Z digest=sha256:7bb869c243511ed7c770c3ab02ac8b4d89603830343eb0087eeade9b0cf8b96c

Observation b8661c60-d874-4eb4-9f44-ef9d627ab16e · outbound

This paper cites Maximum entropy inverse reinforcement learning in continuous state spaces with path integrals.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Maximum entropy inverse reinforcement learning in continuous state spaces with path integrals

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:37.206853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.189840Z digest=sha256:ee396eb7ad6e784081dbf053aa4f0d8b400860dec841ea48c6ac8082ad39ae13

Observation 5835af09-fee6-4db9-8c05-4cea46670e6e · outbound

This paper cites Robotic strategic behavior in adversarial environments.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Robotic strategic behavior in adversarial environments

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:37.197600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.192969Z digest=sha256:d25c5a204b5e83e5498fbf554da899e007a4c672de0889bfc6e1d1baf10f50e0

Observation 237bc520-bc21-404c-a71d-950a8a8cd26c · outbound

This paper cites A survey of inverse reinforcement learning: Challenges, methods and progress.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning A survey of inverse reinforcement learning: Challenges, methods and progress

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T23:23:34.195940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:23:34.195940Z digest=sha256:466362716b574183b93d5be941c345c6da4c1b677675ad6f6c93b501fc92bf02

Observation eb21826c-11ee-4ff1-a64f-76ab77da4b57 · outbound

This paper cites Near-optimal regret bounds for reinforcement learning.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Near-optimal regret bounds for reinforcement learning

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:37.184391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.199023Z digest=sha256:ef1dce7af7d98118ff146b4e5a18c7a1879c24b42686bdb701d79d11b93db7da

Observation f99fbe30-cf8b-462d-9d5a-7a35f636e937 · outbound

This paper cites Partially observable Monte Carlo planning with state variable constraints for mobile robot navigation.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Partially observable Monte Carlo planning with state variable constraints for mobile robot navigation

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:37.047550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.201795Z digest=sha256:f79ff073ea8eb6018dcf31b9db976473d2b37e28ced9bca560eac50a46bb4921

Observation 6321b589-b0fd-43a4-be1a-4f53e07b8d54 · outbound

This paper cites On the complexity of computing maximum entropy for Markovian models.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning On the complexity of computing maximum entropy for Markovian models

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.891114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.204548Z digest=sha256:9db881fd6ddcc0c79ba98a2f3077a91ba74403f90c8196b980d9c4fbf1cf8735

Observation 853c2f91-16b5-4456-baac-c509bb989afa · outbound

This paper cites Exploration-Exploitation Trade-off in Reinforcement Learning on Online Markov Decision Processes with Global Concave Rewards.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Exploration-Exploitation Trade-off in Reinforcement Learning on Online Markov Decision Processes with Global Concave Rewards

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T23:23:34.207057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:23:34.207057Z digest=sha256:ef750915f402c6bca35a4d60a42648e5ff059a4fe6ec8f5c6149204f350b889a

Observation bd2ce924-d366-45e6-a9ce-b8bd095e719c · outbound

This paper cites Decentralized mcts via learned teammate models.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Decentralized mcts via learned teammate models

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.878110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.210173Z digest=sha256:a65c42d8243fc2546f20f2819d6c1deb8aa9582110a1c03d9f75829c1b81e6ec

Observation 1d2aa2fd-b139-4464-8d71-82c0416a4c2a · outbound

This paper cites Target surveillance in adversarial environments using pomdps.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Target surveillance in adversarial environments using pomdps

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.870140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.213184Z digest=sha256:50452fe727820af5da2f785cef1cccb50afdac014087e7b72f6beafd376bb0de

Observation 35515fed-ab01-4576-9f72-8ee4aea4f362 · outbound

This paper cites A comprehensive survey on safe reinforcement learning.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning A comprehensive survey on safe reinforcement learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T23:23:34.215933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:23:34.215933Z digest=sha256:a0e5c6aadbf27d4853ffd7af058eddf7c1e74e354b2d3cc46b57140e2ad9b15b

Observation f72e75a5-fa02-480b-be73-03facff374ab · outbound

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

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Multi-agent deep reinforcement learning: A survey

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.856310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.247836Z digest=sha256:364d179a442772e90d15212a686b53b8c98a63dac1ae2e9d38c626b80d1e5c3a

Observation cc9426ff-1d5c-438c-a8bc-4054e4b999e7 · outbound

This paper cites Towards modeling the behavior of autonomous systems and humans for trusted operations.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Towards modeling the behavior of autonomous systems and humans for trusted operations

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.847845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.330448Z digest=sha256:82eea46ad79cbea9d7d352872144e302d6a929a70447fe42ec71221743aca399

Observation 4272b318-f23b-4ed9-a51d-c46d3baf99fd · outbound

This paper cites Learning others' intentional models in multi-agent settings using interactive POMDP s.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Learning others' intentional models in multi-agent settings using interactive POMDP s

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.838770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.395601Z digest=sha256:eec80a4dd2c5b892d222a028d50cee466f98dcfc1d1eaced07d23702643521bf

Observation c2d19152-75fa-4cde-92bb-dcf42f9d7757 · outbound

This paper cites I POMDP -net: A deep neural network for partially observable multi-agent planning using interactive POMDP s.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning I POMDP -net: A deep neural network for partially observable multi-agent planning using interactive POMDP s

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.789831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.526573Z digest=sha256:e2611e90dc6233f3569987367f122f9b83ee543b4db8173bf63905f45bd4ca9f

Observation 88f74cbc-ca46-4451-a81a-745d5133f276 · outbound

This paper cites A survey of multi-robot regular and adversarial patrolling.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning A survey of multi-robot regular and adversarial patrolling

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.719027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.600271Z digest=sha256:d74bf708b95248b4a4359d4baa0dffa8164484adccb4dee023ab93e5c29ec25f

Observation cd605f81-f030-4041-9e13-1671fd8ed1de · outbound

This paper cites Robust dynamic programming.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Robust dynamic programming

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.710712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.609117Z digest=sha256:ea98ffac3cc11ab0b54497b76967fee3bf8c00b93309c3a3716e36b00735977e

Observation 729ac3a5-e698-4093-af7d-a21d7a9fd2ea · outbound

This paper cites Information theory and statistical mechanics.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Information theory and statistical mechanics

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.702873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.617545Z digest=sha256:9091a6479f393871f8c9d03abbed42c2f8e0b5eecbdd7c40bf1004e2175675a2

Observation 9c09b023-4587-4a7b-829f-7a335f4cb060 · outbound

This paper cites On the rationale of maximum-entropy methods.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning On the rationale of maximum-entropy methods

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.694383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.631358Z digest=sha256:e528d56cdffea682d00b1212cd1e8be895f6e76bff31bafc347c9928347f7cea

Observation 7b7780ce-dbf2-4548-be4e-6e53d88d081a · outbound

This paper cites Efficient dependency-guided named entity recognition.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Efficient dependency-guided named entity recognition

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.684235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.634099Z digest=sha256:4596c3dfdf306c96f4a0c37ecd15495fb18a93c4b5ab4bb51d95dd642e8242d8

Observation cb4405a0-d172-47c2-82e1-0bb4ee4a9d25 · outbound

This paper cites Planning and acting in partially observable stochastic domains.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Planning and acting in partially observable stochastic domains

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.599907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.637022Z digest=sha256:c44fd4b6c44df8c9635c983cd7e9c60221fe7c6337d9eb67db0d9f66a0279ac2

Observation e74ae8d8-3e2e-4dd7-9b73-47b34a394145 · outbound

This paper cites Probabilistic Graphical Models: Principles and Techniques , 2009.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Probabilistic Graphical Models: Principles and Techniques , 2009

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.503610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.639847Z digest=sha256:5c055cd459d25b4f75cfe70f94076c60747b855e6f44d487f2c6f3851fcf8aaf

Observation 751fd561-31de-48d6-846d-71b344acee28 · outbound

This paper cites Review of pedestrian trajectory prediction methods: Comparing deep learning and knowledge-based approaches.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Review of pedestrian trajectory prediction methods: Comparing deep learning and knowledge-based approaches

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.496076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.643721Z digest=sha256:36347b52dd51dfcc6eab1ab21fe7596b09b492553a2c15abe8ebeaf9d7a0ec53

Observation dd76c315-4f77-44d5-a0e4-a0e464d594b7 · outbound

This paper cites Partially observable markov decision processes in robotics: A survey.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Partially observable markov decision processes in robotics: A survey

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.488084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.646552Z digest=sha256:a68d055c3e9bc0094fbc7c465892f916b1e083ad642d56066bf87d81a3c42fd9

Observation a00213d8-a567-432b-accf-f205d5be7d14 · outbound

This paper cites A survey of the Schr\"odinger problem and some of its connections with optimal transport.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning A survey of the Schr\"odinger problem and some of its connections with optimal transport

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T23:23:34.649792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:23:34.649792Z digest=sha256:f61dc644dd3ba091e442347605d91e7b5a3a0c18ed514c3de8a6fd47e9e58d7b

Observation a6bc935f-3512-443d-ad23-bd3e0da2db43 · outbound

This paper cites o dinger.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning o dinger

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.479356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.653260Z digest=sha256:afd9a8e5743a048cf27a08986f2a25662c450fde93de2d9504ae7e5bdb3ba639

Observation 486aba7d-d1d9-4084-91db-805f2814dc19 · outbound

This paper cites Towards applying interactive pomdps to real-world adversary modeling.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Towards applying interactive pomdps to real-world adversary modeling

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.439611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.658019Z digest=sha256:e92b25ee69e94424bb2372fe4ca7dd458030ea8c297548b7f906223c75fc9637

Observation 31304ea1-03ab-49b4-a9ce-9e7bcd24b0bf · outbound

This paper cites Robust control of M arkov decision processes with uncertain transition matrices.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Robust control of M arkov decision processes with uncertain transition matrices

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.360295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.727368Z digest=sha256:41a5c5a07b94163e7cce0417e5b83ecf87099e938f5981447a0333e45c6912c4

Observation 18e53c32-90e1-4a0d-b79e-c594db639797 · outbound

This paper cites Reasoning in Uncertain Adversarial Environments in Agent/Multiagent Systems.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Reasoning in Uncertain Adversarial Environments in Agent/Multiagent Systems

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.351844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.834432Z digest=sha256:dac6a2e45e075bbdc3b977df6237a5b6444ca90fe5784e69ce09cb76601f16ff

Observation 86f5465f-0c97-43c5-b09d-c4c4f7f9021c · outbound

This paper cites Predicting actions to act predictably: Cooperative partial motion planning with maximum entropy models.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Predicting actions to act predictably: Cooperative partial motion planning with maximum entropy models

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.343383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.878769Z digest=sha256:4d750c76b5ccf8439f7de93e6cc3e2380ee4bf58cde946b74aa3ecc3b8b1dcc3

Observation 088a5bb6-a144-454e-8164-269c3eb13a84 · outbound

This paper cites Weathering ongoing uncertainty: Learning and planning in a time-varying partially observable environment.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Weathering ongoing uncertainty: Learning and planning in a time-varying partially observable environment

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.333859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.887759Z digest=sha256:5fc75b29b54a263395391ac5233de9ee1f4676cd7004939aec572935c6e525ca

Observation 78440a96-311e-4ac2-a6f1-f71da6c13cb2 · outbound

This paper cites Enhancing robot navigation policies with task-specific uncertainty management.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Enhancing robot navigation policies with task-specific uncertainty management

Reference 34

Resolution
verified exact
raw_fallback, observed 2026-08-11T23:23:35.489356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.904217Z digest=sha256:a2629aad604f5069cab0232c339570fd19f7e9ccdce4660be6c2b0ad3367ca42

Observation a809f655-7043-43c6-8121-8d82b3528635 · outbound

This paper cites ComTraQ-MPC: Meta-Trained DQN-MPC Integration for Trajectory Tracking with Limited Active Localization Updates.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning ComTraQ-MPC: Meta-Trained DQN-MPC Integration for Trajectory Tracking with Limited Active Localization Updates

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-11T23:23:35.273205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.908150Z digest=sha256:66d145262f946aaf00d0605d671705862d0407f0e46d71b831c64a5a064ef05f

Observation 38cbe8ee-3ec0-45e9-9a84-23bb0129f851 · outbound

This paper cites Adversarial models for opponent intent inferencing.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Adversarial models for opponent intent inferencing

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.275867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.914195Z digest=sha256:e9d41b1e209bce7c56d472348aaea47256bb98fd71faaa420b4d2bdfae88fa2d

Observation 7a0f6dd7-3ff9-4c11-a14c-a3d01d147b98 · outbound

This paper cites Modeling adversarial intent for interactive simulation and gaming: the fused intent system.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Modeling adversarial intent for interactive simulation and gaming: the fused intent system

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.208156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.916610Z digest=sha256:c4c15014eebc59a52d3d8766f3f8500249280499eef9902c1872ca501c99efa3

Observation 477ef7cd-3cb4-4898-ba70-4512cec7bc13 · outbound

This paper cites Entropy maximization for constrained Markov decision processes.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Entropy maximization for constrained Markov decision processes

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.199756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.919698Z digest=sha256:08359ae6bd36282493c826f07a01da70193ceb86ddd2642c630f5f544e1409d7

Observation fcb430ab-3df6-4ffc-992d-832dbb61967d · outbound

This paper cites Entropy maximization for Markov decision processes under temporal logic constraints.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Entropy maximization for Markov decision processes under temporal logic constraints

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.191155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.922641Z digest=sha256:acd4bf0d24351300c5e8409ef21612f86d32ac69c93d985c9daf586ccc96429b

Observation 45f7f801-c6a5-4e0a-aa55-cbd0ec67d4ca · outbound

This paper cites A survey of point-based POMDP solvers.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning A survey of point-based POMDP solvers

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.183547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.925411Z digest=sha256:ca046e66cd86bdce6bbf8872ca3d47515707f3f83965bda3c7ad5e25a9acda84

Observation 4100b902-d2a7-4eea-8017-4fab8b13b554 · outbound

This paper cites Monte-carlo planning in large POMDP s.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Monte-carlo planning in large POMDP s

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.054596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.928290Z digest=sha256:8226d8fcbe08aef7ce591132af66c7e4f867677b65f359336b7b249c7babc726

Observation a8db4f14-b875-4a63-b892-fa6da82d1a8d · outbound

This paper cites Despot: O nline POMDP planning with regularization.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Despot: O nline POMDP planning with regularization

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.029683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.930456Z digest=sha256:3d21bad68640cafd9f5c14ffe50c641f0447fb37178d7faf759f8e7705ac4608

Observation 853236ab-09bf-4aa5-a236-8eb9a2e8d8ad · outbound

This paper cites Elements of Information Theory.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Elements of Information Theory

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.020146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.932755Z digest=sha256:125d3f888e5137c3ddaede499908a2c53f7d2b9850efd33c273ecdfe32a4bced

Observation f0e4113e-efca-46a9-93e7-0093ced32f21 · outbound

This paper cites Monte carlo pomdps.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Monte carlo pomdps

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:36.012750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.935104Z digest=sha256:0e842dccd8deb926714ed2d5e167a388b7169e82bd7747bd865d6c765933039b

Observation ec864fd2-94ae-45dc-8d27-69510ceef960 · outbound

This paper cites Efficient computation of optimal actions.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Efficient computation of optimal actions

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:35.904554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.937476Z digest=sha256:3350f0b82e6f911485653bce4604045e013e95c1c55a00070b4179bb31949c0a

Observation f6d86876-e781-418e-93a9-493d991d96f4 · outbound

This paper cites Robust markov decision processes.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Robust markov decision processes

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:35.803165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.940052Z digest=sha256:0daf5309b61074f2e0429df559cf5361e0762e68c375221663b422cf93903cfd

Observation c9984c1e-5b5d-49c7-b0a9-41bf196fa032 · outbound

This paper cites Robust Markov Decision Processes without Model Estimation.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Robust Markov Decision Processes without Model Estimation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T23:23:34.942702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T23:23:34.942702Z digest=sha256:69456fcdadb47fd9fa333ae9293faf0ca5bda0c762163fbf22367358eac6b57d

Observation 57d671af-a6b7-4d5f-8155-e28bcebaa515 · outbound

This paper cites Robust deep reinforcement learning against adversarial perturbations on state observations.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Robust deep reinforcement learning against adversarial perturbations on state observations

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:35.794192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:34.971797Z digest=sha256:5a37bcf2ea45f774cb9eec2b26c3c6aa0a40d194b2429af2b1d5b6d90484d197

Observation 84231b86-1780-4d1f-8638-f40b17b944b4 · outbound

This paper cites Multi-robot coordination and planning in uncertain and adversarial environments.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Multi-robot coordination and planning in uncertain and adversarial environments

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:35.784176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:35.044297Z digest=sha256:184b2de6e088e6509f75c5e5fa58b3db1d1b19258b285b8db642bf9913e37c70

Observation c52b2bb5-35be-4c4d-b586-3896b952fa6f · outbound

This paper cites Maximum entropy inverse reinforcement learning.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Maximum entropy inverse reinforcement learning

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:35.774190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:35.139360Z digest=sha256:0ce40295ecd273a60ae5bbc4541308f36c4861def1c71eff27582d2417fc6103

Observation 5d3c731d-d75b-4bb0-8930-377fd102b3a9 · outbound

This paper cites Planning-based prediction for pedestrians.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Planning-based prediction for pedestrians

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:35.648763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:35.235444Z digest=sha256:4157fad7612896e414b40d4ce08c4950bc5d60f452e8c35c1c2bcb180fa5007a

Observation 3477f37a-e5fc-455a-a47b-f8056b2d24cc · outbound

This paper cites The adversarial activity model for bounded rational agents.

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning The adversarial activity model for bounded rational agents

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T23:23:35.597324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T23:23:35.238983Z digest=sha256:b22906850d5f9618c1d0b0f62be193127c757fc46be051b1031784751ab2a7a8

Pith citing papers

Observation 798c3d61-a6ec-4986-8b7f-215335f38e62 · inbound

Enhancing Robot Navigation Policies with Task-Specific Uncertainty Managements cites this paper.

Enhancing Robot Navigation Policies with Task-Specific Uncertainty Managements TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:12:51.214540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:12:51.061553Z digest=sha256:37735c963dafad358bf48ed8aba6526539996b8a91ba2c2415f9bc62e8624679