Paper Citation Record · LEDGER

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

As of 16 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 2026-08-15T06:32:42.880941+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
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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.