AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration | Paper Citation Record

Observation 0bf1536c-2817-4943-b2c5-d393bf190298 · outbound

This paper cites Group hunting within the carnivora: physiological, cognitive and environmental influences on strategy and cooperation,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Group hunting within the carnivora: physiological, cognitive and environmental influences on strategy and cooperation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.886998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bddaf62a-fdf9-4bdc-886b-b00a2d9f7aff · outbound

This paper cites Intercepting rogue robots: An algorithm for capturing multiple evaders with multiple pursuers,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Intercepting rogue robots: An algorithm for capturing multiple evaders with multiple pursuers,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.888955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation df8213c9-dee9-4930-9a07-9c30bbf1149a · outbound

This paper cites Adaptive partitioning for coordinated multi-agent perimeter defense,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Adaptive partitioning for coordinated multi-agent perimeter defense,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.903325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 367b4b2d-2fdd-476c-9c42-975e60e17546 · outbound

This paper cites Multi-usv cooperative chasing strategy based on obstacles assistance and deep reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Multi-usv cooperative chasing strategy based on obstacles assistance and deep reinforcement learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.897653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ab7be8b9-18fa-4377-bc76-a93dd6f88aa1 · outbound

This paper cites Poaching detection technologies—a survey,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Poaching detection technologies—a survey,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.885067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8d58b4f4-3fea-40c4-a983-35693516bc27 · outbound

This paper cites Uav-ugv-umv multi-swarms for cooperative surveillance,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Uav-ugv-umv multi-swarms for cooperative surveillance,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.881322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a5434687-328a-4daa-9b1b-cb4697fbd6e2 · outbound

This paper cites A game of cops and robbers,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration A game of cops and robbers,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.883150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8a967af0-1a8b-45be-9e50-97eabca2dcea · outbound

This paper cites Multiple pursuer multiple evader differential games,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Multiple pursuer multiple evader differential games,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.899393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0f793463-f75b-4f07-ae72-b11b6cabbf18 · outbound

This paper cites Bonato,The game of cops and robbers on graphs.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Bonato,The game of cops and robbers on graphs

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.900219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ea22da95-f1c9-4e7f-9f47-2c5ad282cdcc · outbound

This paper cites A visibility roadmap sampling approach for a multi- robot visibility-based pursuit-evasion problem,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration A visibility roadmap sampling approach for a multi- robot visibility-based pursuit-evasion problem,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.902179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 98d81c7a-dc88-41ba-9ae7-d5c66122dbd4 · outbound

This paper cites Distributed encirclement and capture of multiple pursuers with collision avoidance,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Distributed encirclement and capture of multiple pursuers with collision avoidance,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.890533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dfabbeb6-0a5e-4738-b67b-a19dba47f16c · outbound

This paper cites Cooperative pursuit with voronoi partitions,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Cooperative pursuit with voronoi partitions,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.894787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5125b912-618b-483e-ba92-5f4ac621c19b · outbound

This paper cites Group chasing tactics: how to catch a faster prey,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Group chasing tactics: how to catch a faster prey,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.901153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b1cc7371-1906-45b5-9cd7-f99d8239b10f · outbound

This paper cites Multi-agent actor-critic for mixed cooperative-competitive environ- ments,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Multi-agent actor-critic for mixed cooperative-competitive environ- ments,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.907114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3e369e13-0d7b-4409-8580-20e3a52bfbac · outbound

This paper cites On developing a uav pursuit-evasion policy using reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration On developing a uav pursuit-evasion policy using reinforcement learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.884291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f33e8fa6-7066-45f2-87c3-e5b8912768fb · outbound

This paper cites Emergent behaviors in multiagent pursuit evasion games within a bounded 2d grid world,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Emergent behaviors in multiagent pursuit evasion games within a bounded 2d grid world,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.880597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation afa68010-5d1c-4181-838d-fd422111d439 · outbound

This paper cites Modeling and analysis of cooperative pursuit actions in two-dimensional multi-agent pursuit-evasion games,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Modeling and analysis of cooperative pursuit actions in two-dimensional multi-agent pursuit-evasion games,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.878359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1ba8904a-e1e4-4699-958a-c603039d6f5c · outbound

This paper cites A survey of the pursuit– evasion problem in swarm intelligence,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration A survey of the pursuit– evasion problem in swarm intelligence,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.882374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2f8328a8-8c61-49cd-9ba4-4516412da0c1 · outbound

This paper cites Pursuit-evasion of an evader by multiple pur- suers,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Pursuit-evasion of an evader by multiple pur- suers,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.886212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 22089e82-8d10-490e-825f-d046d4179dbc · outbound

This paper cites A dimension-reduction solution of free-time differential games for spacecraft pursuit-evasion,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration A dimension-reduction solution of free-time differential games for spacecraft pursuit-evasion,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.810021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5e347f82-b3d9-426d-9b7c-0832592a56c9 · outbound

This paper cites Differential games. a mathematical theory with applications to warfare and pursuit, control and optimization.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Differential games. a mathematical theory with applications to warfare and pursuit, control and optimization

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.873097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0657a238-4578-4b3f-87cd-fc333ad30706 · outbound

This paper cites Isaacs,Differential games: a mathematical theory with applications to warfare and pursuit, control and optimization.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Isaacs,Differential games: a mathematical theory with applications to warfare and pursuit, control and optimization

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.875310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 46610a83-ee76-4325-beb9-8e02d067ae34 · outbound

This paper cites Pursuit-evasion differential games of players with different speeds in spaces of different dimensions,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Pursuit-evasion differential games of players with different speeds in spaces of different dimensions,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.870863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e9b3a636-7749-46bc-ad05-c3a611b29cb3 · outbound

This paper cites Encirclement guaranteed cooperative pursuit with robust model predictive control,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Encirclement guaranteed cooperative pursuit with robust model predictive control,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.888536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4b73f289-3c60-4531-a735-cf84e5e7039c · outbound

This paper cites Cooperative pursuit with multi-pursuer and one faster free-moving evader,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Cooperative pursuit with multi-pursuer and one faster free-moving evader,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.905151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d73475ca-2716-468b-b5c9-2862df487b3a · outbound

This paper cites Game-theoretic utility tree for multi-robot cooperative pursuit strategy,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Game-theoretic utility tree for multi-robot cooperative pursuit strategy,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.858276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 19f48060-7083-4cdd-ae3a-adf14d04a356 · outbound

This paper cites Fg-pe: Factor-graph approach for multi-robot pursuit-evasion,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Fg-pe: Factor-graph approach for multi-robot pursuit-evasion,

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:26:53.891161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2f1e59a9-dc97-4530-bc81-5596f13cd2bf · outbound

This paper cites Decentralized multi-agent pursuit using deep reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Decentralized multi-agent pursuit using deep reinforcement learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.879521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cc2d88b6-dd70-408b-aa97-902977c467a3 · outbound

This paper cites Cooperative control for multi-player pursuit-evasion games with reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Cooperative control for multi-player pursuit-evasion games with reinforcement learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.842432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d7d15d15-b345-47e8-9bf2-e05c09d82107 · outbound

This paper cites Pursuit-Evasion for Car-like Robots with Sensor Constraints.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Pursuit-Evasion for Car-like Robots with Sensor Constraints

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:26:53.880038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 41227e55-784f-473c-af5f-960a3e8a34f2 · outbound

This paper cites Pursuit-evasion with decen- tralized robotic swarm in continuous state space and action space via deep reinforcement learning.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Pursuit-evasion with decen- tralized robotic swarm in continuous state space and action space via deep reinforcement learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.834880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation af3931f6-b7b2-4e61-ba25-6a63534bbffc · outbound

This paper cites On discrete-time pursuit-evasion games with sensing limitations,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration On discrete-time pursuit-evasion games with sensing limitations,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.836686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c5023587-75a9-4179-85f1-9a1a20a0bcf3 · outbound

This paper cites Distributed pursuit of an evader with collision and obstacle avoidance,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Distributed pursuit of an evader with collision and obstacle avoidance,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.829419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2031fcfe-21a8-422f-a662-ad3837c2adec · outbound

This paper cites Decentralized multi-robot pursuit of an evader in obstacle environments,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Decentralized multi-robot pursuit of an evader in obstacle environments,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.831355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a67259ca-3be0-4c83-9576-c31fc02c9fc0 · outbound

This paper cites Pursuit winning strategies for reach-avoid games with polygonal obstacles,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Pursuit winning strategies for reach-avoid games with polygonal obstacles,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.833102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b0e76e4d-7f96-49cc-9423-1e15d329a80f · outbound

This paper cites Pursuit-evasion problems of multi- agent systems in cluttered environments,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Pursuit-evasion problems of multi- agent systems in cluttered environments,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.844432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dd8d23d6-0e8c-4ad9-9cf4-aaa977e7f149 · outbound

This paper cites Probabilistic strategies for pursuit in cluttered environments with multiple robots,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Probabilistic strategies for pursuit in cluttered environments with multiple robots,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.853913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 52eef6a0-c2b0-4f3a-ba5d-cda3b70590ec · outbound

This paper cites Game of drones: Multi-uav pursuit-evasion game with online motion planning by deep reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Game of drones: Multi-uav pursuit-evasion game with online motion planning by deep reinforcement learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.834008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation af0835a0-ad87-49e5-ae19-e111ed376929 · outbound

This paper cites Multi-uav pursuit-evasion with online planning in unknown environments by deep reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Multi-uav pursuit-evasion with online planning in unknown environments by deep reinforcement learning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.835788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 18ba719e-48ff-4d7d-9eac-4c777304b133 · outbound

This paper cites Multi-target pursuit by a decentralized heterogeneous uav swarm using deep multi- agent reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Multi-target pursuit by a decentralized heterogeneous uav swarm using deep multi- agent reinforcement learning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.839566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b9ae292c-1767-4bf8-bf76-211c2ccbe1c9 · outbound

This paper cites Multi-robot cooperative pursuit via potential field-enhanced reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Multi-robot cooperative pursuit via potential field-enhanced reinforcement learning,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.904581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 270aa312-3872-40ba-b8c1-3879ae9b8a13 · outbound

This paper cites Pursuit-evasion game strategy of usv based on deep reinforcement learning in complex multi-obstacle environment,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Pursuit-evasion game strategy of usv based on deep reinforcement learning in complex multi-obstacle environment,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.846400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f95a3a8c-cb8a-47c2-808b-7117ec78cba5 · outbound

This paper cites Viper: Visibility-based pursuit-evasion via reinforcement learning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Viper: Visibility-based pursuit-evasion via reinforcement learning,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.818077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c2c794d0-9114-4015-997c-1d0e014afd24 · outbound

This paper cites Toward multi-target self-organizing pursuit in a partially observable markov game,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Toward multi-target self-organizing pursuit in a partially observable markov game,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.865324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 518ae81d-27d6-4645-8a02-2cf5886b18aa · outbound

This paper cites MatrixWorld: A pursuit-evasion platform for safe multi-agent coordination and autocurricula.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration MatrixWorld: A pursuit-evasion platform for safe multi-agent coordination and autocurricula

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:26:53.888612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 767784c8-0e7b-4e53-a0a7-cfb4e9b9cf46 · outbound

This paper cites Distributed pursuit-evasion without mapping or global localization via local frontiers,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Distributed pursuit-evasion without mapping or global localization via local frontiers,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.856149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f6f6527c-ea2b-4118-8016-b1d501c99619 · outbound

This paper cites Gurobi Optimizer Reference Manual.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Gurobi Optimizer Reference Manual

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.863047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 721a7d72-cf9b-41c1-92d0-44310c36bfd3 · outbound

This paper cites Belief state monte carlo planning for multi-agent visibility-based pursuit-evasion,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Belief state monte carlo planning for multi-agent visibility-based pursuit-evasion,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.868077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 13693fe4-2156-486a-9ee9-023c20284321 · outbound

This paper cites Holistically Guided Monte Carlo Tree Search for Intricate Information Seeking.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Holistically Guided Monte Carlo Tree Search for Intricate Information Seeking

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:26:53.882726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d86c87a0-6c5f-4de2-a90e-d0f0c7a1d34d · outbound

This paper cites Decentralized control strategies for unmanned aircraft system pursuit and evasion,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Decentralized control strategies for unmanned aircraft system pursuit and evasion,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.909004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c2a595e-27ff-427a-8ca5-b2bfd916f4bd · outbound

This paper cites Bandit based monte-carlo planning,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Bandit based monte-carlo planning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.911086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b40488ae-fb35-4541-a2e9-f6ae5675ee68 · outbound

This paper cites How powerful are graph neural networks?.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration How powerful are graph neural networks?

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.895265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2ec6bdd1-1f12-4786-a3ac-49c5564b27a4 · outbound

This paper cites Graph Attention Networks.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Graph Attention Networks

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-07-02T11:26:53.885954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 202c8e73-8878-46a5-a62e-dd147004c8b8 · outbound

This paper cites Traversing mars: Cooperative informative path planning to efficiently navigate unknown scenes,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Traversing mars: Cooperative informative path planning to efficiently navigate unknown scenes,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.825733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 427d282f-2309-468e-9467-123f124310fb · outbound

This paper cites Novel implementation of multi-robot space exploration utilizing coordinated multi-robot exploration and frequency modified whale optimization algorithm,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Novel implementation of multi-robot space exploration utilizing coordinated multi-robot exploration and frequency modified whale optimization algorithm,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.849963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6449cf32-a555-4084-9631-be5dce28739f · outbound

This paper cites Accelerated k-serial stable coalition for dynamic capture and resource defense,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Accelerated k-serial stable coalition for dynamic capture and resource defense,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.814021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a998b89c-c2fa-41a1-9458-624f2e2a9153 · outbound

This paper cites A visibility graph approach for path planning and real-time collision avoidance on maritime unmanned systems,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration A visibility graph approach for path planning and real-time collision avoidance on maritime unmanned systems,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.812169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 32b2e043-8a53-4e91-acde-0222f2a540e5 · outbound

This paper cites Optimal reciprocal collision avoidance for multi-agent navigation,.

AMBUSH: Collaborative Capture in Complex Environments with Neural Acceleration Optimal reciprocal collision avoidance for multi-agent navigation,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T03:01:53.810214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers