Make Planning Research Rigorous Again! | Paper Citation Record

Observation 93e3571b-2f77-40f2-b13f-29fb5d6b30e8 · outbound

This paper cites Oversubscription planning: Complexity and compilabil- ity.

Make Planning Research Rigorous Again! Oversubscription planning: Complexity and compilabil- ity

Reference 1

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Observation d1d34f55-410e-4f79-a4d6-546da2258afb · outbound

This paper cites Translating HTNs to PDDL: A small amount of domain knowledge can go a long way.

Make Planning Research Rigorous Again! Translating HTNs to PDDL: A small amount of domain knowledge can go a long way

Reference 2

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Observation 0975c732-3778-4a3a-bd1c-d9cc6ad06688 · outbound

This paper cites The AIPS’00 planning competition.AI Magazine, 22(3):47–56, 2001.

Make Planning Research Rigorous Again! The AIPS’00 planning competition.AI Magazine, 22(3):47–56, 2001

Reference 3

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Observation fb00cfd8-4133-495d-89f5-5bd622543a73 · outbound

This paper cites Planning for temporally extended goals.Annals of Mathematics and Artificial Intelligence, 22(1,1):5–27, 1998.

Make Planning Research Rigorous Again! Planning for temporally extended goals.Annals of Mathematics and Artificial Intelligence, 22(1,1):5–27, 1998

Reference 4

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Observation a52552b7-d360-42fd-9384-df747eabb5b2 · outbound

This paper cites Planning in polynomial time: the SAS-PUBS class.

Make Planning Research Rigorous Again! Planning in polynomial time: the SAS-PUBS class

Reference 5

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Observation 2275ee2c-8c7d-4118-9372-04fdea943504 · outbound

This paper cites Complexity results for SAS + planning.Computa- tional Intelligence, 11(4):625–655, 1995.

Make Planning Research Rigorous Again! Complexity results for SAS + planning.Computa- tional Intelligence, 11(4):625–655, 1995

Reference 6

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Observation 57733c53-5f45-4509-a5a1-865cbdde9ef3 · outbound

This paper cites Baier and Sheila A.

Make Planning Research Rigorous Again! Baier and Sheila A

Reference 7

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Observation 489edc52-cc1d-443e-93b2-9b3baae1f0ec · outbound

This paper cites Baier and Sheila A.

Make Planning Research Rigorous Again! Baier and Sheila A

Reference 8

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Observation d12649ff-3648-4805-8f46-f6f320541be4 · outbound

This paper cites an unresolved cited work.

Make Planning Research Rigorous Again! Unresolved cited work

Reference 9

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Observation 9ef94480-26a4-42c5-8e51-691d232c3bd3 · outbound

This paper cites Planning with incomplete information as heuristic search in belief space.

Make Planning Research Rigorous Again! Planning with incomplete information as heuristic search in belief space

Reference 10

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Observation 024eb2e0-dc61-4abd-9bf3-7aa6cee35083 · outbound

This paper cites Benchagents: Automated benchmark creation with agent interaction.arXiv preprint arXiv:2410.22584, 2024.

Make Planning Research Rigorous Again! Benchagents: Automated benchmark creation with agent interaction.arXiv preprint arXiv:2410.22584, 2024

Reference 11

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Observation 9458b4dc-22dc-4cd1-87d6-6eefedb17db7 · outbound

This paper cites The computational complexity of propositional STRIPS planning.Artificial Intelligence, 69(1–2):165–204, 1994.

Make Planning Research Rigorous Again! The computational complexity of propositional STRIPS planning.Artificial Intelligence, 69(1–2):165–204, 1994

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:25.014935Z

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Observation 77c57375-0004-42b8-af8d-f58727378e4e · outbound

This paper cites Act local, think global: Width notions for tractable planning.

Make Planning Research Rigorous Again! Act local, think global: Width notions for tractable planning

Reference 13

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Observation b0af2800-d45a-466e-8483-1a1f728a9d28 · outbound

This paper cites Completeness and optimality preserving reduction for planning.

Make Planning Research Rigorous Again! Completeness and optimality preserving reduction for planning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:25.312273Z

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Observation b2e54da6-d07e-401a-a9bc-9f10aa74a4d7 · outbound

This paper cites Planning via model checking: A decision procedure forAR.

Make Planning Research Rigorous Again! Planning via model checking: A decision procedure forAR

Reference 15

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Observation 386b4e97-17a8-44bc-a022-e9d81524669e · outbound

This paper cites an unresolved cited work.

Make Planning Research Rigorous Again! Unresolved cited work

Reference 16

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Observation f0169d87-1d01-4c2e-bd49-542c822501ea · outbound

This paper cites Textworld: A learning environment for text-based games.

Make Planning Research Rigorous Again! Textworld: A learning environment for text-based games

Reference 17

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Observation 753c3a79-05cf-426a-81c6-4aa47fa31da8 · outbound

This paper cites Culberson.

Make Planning Research Rigorous Again! Culberson

Reference 18

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Observation cce26515-39aa-4f03-83d1-2d48163b757c · outbound

This paper cites an unresolved cited work.

Make Planning Research Rigorous Again! Unresolved cited work

Reference 19

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Observation 3b160270-3c3f-4b54-bcdc-1996e7a3fe3d · outbound

This paper cites Generalized best-first search strategies and the optimality of A∗.Journal of the ACM, 32(3):505–536, 1985.

Make Planning Research Rigorous Again! Generalized best-first search strategies and the optimality of A∗.Journal of the ACM, 32(3):505–536, 1985

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:26.143262Z

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Observation ac81aa05-1c24-45b2-be83-939b56ddb8dc · outbound

This paper cites Planning as a service.

Make Planning Research Rigorous Again! Planning as a service

Reference 21

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Observation 5abce7b9-ffaa-4a59-9ec2-ea59bc5419d7 · outbound

This paper cites Novelty vs.

Make Planning Research Rigorous Again! Novelty vs

Reference 22

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Observation 1dca8014-1df5-45c2-907c-297cf46675ea · outbound

This paper cites Probabilistic planning via heuristic forward search and weighted model counting.Journal of Artificial Intelligence Research, 30:565–620, 2007.

Make Planning Research Rigorous Again! Probabilistic planning via heuristic forward search and weighted model counting.Journal of Artificial Intelligence Research, 30:565–620, 2007

Reference 23

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Observation 1591aa81-e8e9-4278-9d05-d9343c4315d0 · outbound

This paper cites Deterministic oversubscription planning as heuristic search: Abstractions and reformulations.Journal of Artificial Intelligence Research, 52: 97–169, 2015.

Make Planning Research Rigorous Again! Deterministic oversubscription planning as heuristic search: Abstractions and reformulations.Journal of Artificial Intelligence Research, 52: 97–169, 2015

Reference 24

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Observation 6343c02e-7c90-4f78-a99f-35fc7f164517 · outbound

This paper cites Red-black planning: A new systematic approach to partial delete relaxation.Artificial Intelligence, 221:73–114, 2015.

Make Planning Research Rigorous Again! Red-black planning: A new systematic approach to partial delete relaxation.Artificial Intelligence, 221:73–114, 2015

Reference 25

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Observation a975a709-5ce6-4219-a14f-aba148acadbb · outbound

This paper cites SOKOBAN and other motion planning problems.Computational Geometry, 13:215–228, 1999.

Make Planning Research Rigorous Again! SOKOBAN and other motion planning problems.Computational Geometry, 13:215–228, 1999

Reference 26

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Observation edf31885-f830-4728-897a-e3b539cd6c2a · outbound

This paper cites Planning with pattern databases.

Make Planning Research Rigorous Again! Planning with pattern databases

Reference 27

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Observation cc1061ad-fac3-47de-a489-9580a3cd37cf · outbound

This paper cites PDDL2.2: The language for the classical part of the 4th International Planning Competition.

Make Planning Research Rigorous Again! PDDL2.2: The language for the classical part of the 4th International Planning Competition

Reference 28

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Observation 421c550d-4067-4c08-b59f-921b4e91a791 · outbound

This paper cites Hendler, and Dana S.

Make Planning Research Rigorous Again! Hendler, and Dana S

Reference 29

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Observation 5218147d-b578-488c-9ca6-4f4c2ffb2947 · outbound

This paper cites Fikes and Nils J.

Make Planning Research Rigorous Again! Fikes and Nils J

Reference 30

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Observation f6108705-134a-4d61-8673-4e8b24659d7a · outbound

This paper cites The detection and exploitation of symmetry in planning problems.

Make Planning Research Rigorous Again! The detection and exploitation of symmetry in planning problems

Reference 31

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Observation c0e6e4c5-9641-48af-ac8b-7204ca8cc42f · outbound

This paper cites PDDL2.1: An extension to PDDL for expressing temporal planning domains.Journal of Artificial Intelligence Research, 20:61–124, 2003.

Make Planning Research Rigorous Again! PDDL2.1: An extension to PDDL for expressing temporal planning domains.Journal of Artificial Intelligence Research, 20:61–124, 2003

Reference 32

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Observation 9d4cad18-8996-4b3e-81e9-00ef3027400e · outbound

This paper cites Tarski: An AI planning modeling framework.https://github.com/aig-upf/tarski, 2018.

Make Planning Research Rigorous Again! Tarski: An AI planning modeling framework.https://github.com/aig-upf/tarski, 2018

Reference 33

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Observation 68b6b18a-d3e6-44a3-9631-28a24a70f2bc · outbound

This paper cites Stream of Search (SoS): Learning to Search in Language.

Make Planning Research Rigorous Again! Stream of Search (SoS): Learning to Search in Language

Reference 34

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Observation bbf0f58a-b1cb-4077-ade1-15ce93f12e46 · outbound

This paper cites Functional Strips: A more flexible language for planning and problem solving.

Make Planning Research Rigorous Again! Functional Strips: A more flexible language for planning and problem solving

Reference 35

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Observation f0b4fdb0-be4f-48cc-acd7-5b29b84855a0 · outbound

This paper cites Gerevini, Patrik Haslum, Derek Long, Alessandro Saetti, and Yannis Dimopou- los.

Make Planning Research Rigorous Again! Gerevini, Patrik Haslum, Derek Long, Alessandro Saetti, and Yannis Dimopou- los

Reference 36

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Observation d1623ba9-21e4-4e94-997f-e500d2989a07 · outbound

This paper cites Gerevini, Alessandro Saetti, and Ivan Serina.

Make Planning Research Rigorous Again! Gerevini, Alessandro Saetti, and Ivan Serina

Reference 37

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Observation 08f16aad-ebbb-49a8-b9df-049589afbde9 · outbound

This paper cites NL2Plan: Robust LLM-driven planning from minimal text descriptions.

Make Planning Research Rigorous Again! NL2Plan: Robust LLM-driven planning from minimal text descriptions

Reference 38

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Observation e57612de-c68f-446d-9907-4ebce460c1b0 · outbound

This paper cites Nau, and Paolo Traverso.Automated planning - theory and practice.

Make Planning Research Rigorous Again! Nau, and Paolo Traverso.Automated planning - theory and practice

Reference 39

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Observation d67de6ac-a6c3-413a-81fb-a87012eca6ed · outbound

This paper cites Nau, and Paolo Traverso.Automated Planning and Acting.

Make Planning Research Rigorous Again! Nau, and Paolo Traverso.Automated Planning and Acting

Reference 40

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Observation f8a5c8af-bc02-45b6-bef5-54b08c3b6edb · outbound

This paper cites an unresolved cited work.

Make Planning Research Rigorous Again! Unresolved cited work

Reference 41

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Observation a35460b7-47f7-4540-8843-f59fe05bc737 · outbound

This paper cites Actionrea- soningbench: Reasoning about actions with and without ramification constraints.

Make Planning Research Rigorous Again! Actionrea- soningbench: Reasoning about actions with and without ramification constraints

Reference 42

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Observation 165cf9b8-042b-4257-9087-1d9f47613c31 · outbound

This paper cites Hart, Nils J.

Make Planning Research Rigorous Again! Hart, Nils J

Reference 43

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Observation cbf1aa97-2058-4ba7-92da-e04f390d07e4 · outbound

This paper cites INV AL: the Independent PDDL plan Validator.https://github.com/ patrikhaslum/INVAL, 2016.

Make Planning Research Rigorous Again! INV AL: the Independent PDDL plan Validator.https://github.com/ patrikhaslum/INVAL, 2016

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:45.800271Z

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Observation b0f565b0-bf02-4d9d-b376-7b59d7dad49d · outbound

This paper cites Morgan & Claypool, 2019.

Make Planning Research Rigorous Again! Morgan & Claypool, 2019

Reference 45

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Observation f11772be-80c9-4eb1-a5dd-d6e1764b8f6c · outbound

This paper cites Exploring the capacity of pretrained language models for reasoning about actions and change.

Make Planning Research Rigorous Again! Exploring the capacity of pretrained language models for reasoning about actions and change

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:45.648486Z

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Observation 58f42ec6-813f-438a-bfae-e36f814d26cc · outbound

This paper cites Hearn and Erik D.

Make Planning Research Rigorous Again! Hearn and Erik D

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:45.520651Z

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Observation 4daba5cc-f806-424b-89ca-60e28d36c40a · outbound

This paper cites Decidability and undecidability results for planning with numerical state variables.

Make Planning Research Rigorous Again! Decidability and undecidability results for planning with numerical state variables

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:45.410212Z

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Observation 3c8ae418-955b-42da-929b-6ea43de2948b · outbound

This paper cites Complexity results for standard benchmark domains in planning.Artificial Intelligence, 143(2):219–262, 2003.

Make Planning Research Rigorous Again! Complexity results for standard benchmark domains in planning.Artificial Intelligence, 143(2):219–262, 2003

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:45.312861Z

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Observation 7a875af9-bd79-4d49-a632-6690bfedc8de · outbound

This paper cites New complexity results for classical planning benchmarks.

Make Planning Research Rigorous Again! New complexity results for classical planning benchmarks

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:45.212378Z

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Observation b09b1cd0-8634-4d2f-8070-b76fb9574623 · outbound

This paper cites The Fast Downward planning system.Journal of Artificial Intelligence Research, 26:191–246, 2006.

Make Planning Research Rigorous Again! The Fast Downward planning system.Journal of Artificial Intelligence Research, 26:191–246, 2006

Reference 51

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Observation 0a776d9f-e788-4dc2-a3d3-244c574934be · outbound

This paper cites Concise finite-domain representations for PDDL planning tasks.Artificial Intelligence, 173:503–535, 2009.

Make Planning Research Rigorous Again! Concise finite-domain representations for PDDL planning tasks.Artificial Intelligence, 173:503–535, 2009

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:45.054858Z

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Observation 687c3020-94b6-4dc2-981f-57ef4e2ba92c · outbound

This paper cites The FF planning system: Fast plan generation through heuristic search.Journal of Artificial Intelligence Research, 14:253–302, 2001.

Make Planning Research Rigorous Again! The FF planning system: Fast plan generation through heuristic search.Journal of Artificial Intelligence Research, 14:253–302, 2001

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:30.171544Z

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Observation f7ed8b80-e2ff-4688-93f1-4e042125c971 · outbound

This paper cites HTN-MAKER: Learning HTNs with minimal additional knowledge engineering required.

Make Planning Research Rigorous Again! HTN-MAKER: Learning HTNs with minimal additional knowledge engineering required

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:30.261588Z

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Observation 8fe8149d-d2fe-496c-b1ad-8b61edfdbc9a · outbound

This paper cites Learning hierarchical task networks for nondeterministic planning domains.

Make Planning Research Rigorous Again! Learning hierarchical task networks for nondeterministic planning domains

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:44.879052Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 177225b9-5d2b-4168-8e37-174972be9071 · outbound

This paper cites Learning methods to generate good plans: Integrating HTN learning and reinforcement learning.

Make Planning Research Rigorous Again! Learning methods to generate good plans: Integrating HTN learning and reinforcement learning

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:44.689656Z

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Observation e347926d-e371-4b91-90d9-e874d777744d · outbound

This paper cites V AL’s progress: The automatic validation tool for PDDL2.1 used in the International Planning Competition.

Make Planning Research Rigorous Again! V AL’s progress: The automatic validation tool for PDDL2.1 used in the International Planning Competition

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:44.531943Z

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Observation 75cb04e7-e86e-48a1-a087-e94fae70b20d · outbound

This paper cites Text2World: Benchmarking Large Language Models for Symbolic World Model Generation.

Make Planning Research Rigorous Again! Text2World: Benchmarking Large Language Models for Symbolic World Model Generation

Reference 58

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Observation ffdbf38c-09dc-4e1c-9e33-9758a7939460 · outbound

This paper cites Tractable plan existence does not imply tractable plan generation.Annals of Mathematics and Artificial Intelligence, 22(3,4):281–296, 1998.

Make Planning Research Rigorous Again! Tractable plan existence does not imply tractable plan generation.Annals of Mathematics and Artificial Intelligence, 22(3,4):281–296, 1998

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:44.328003Z

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Observation fae9d095-5d16-4f23-b750-30794bb25e4c · outbound

This paper cites Corrêa, Florian Pommerening, and Gabriele Röger.

Make Planning Research Rigorous Again! Corrêa, Florian Pommerening, and Gabriele Röger

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:44.158227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8971fedd-b28e-4704-bb6e-7c5cad24fad9 · outbound

This paper cites New islands of tractability of cost-optimal planning.

Make Planning Research Rigorous Again! New islands of tractability of cost-optimal planning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:44.007093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 64064a7c-c542-49ac-94a0-42ab99a10a75 · outbound

This paper cites Implicit abstraction heuristics.Journal of Artificial Intelligence Research, 39:51–126, 2010.

Make Planning Research Rigorous Again! Implicit abstraction heuristics.Journal of Artificial Intelligence Research, 39:51–126, 2010

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:43.824844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c224e3c0-3e85-40c4-b11c-74aeeb771531 · outbound

This paper cites In search of tractability for partial satisfaction planning.

Make Planning Research Rigorous Again! In search of tractability for partial satisfaction planning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:43.645533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eb7dc9ba-7d6a-4a8f-bd24-1e6ce8813339 · outbound

This paper cites Thought of search: Planning with language models through the lens of efficiency.

Make Planning Research Rigorous Again! Thought of search: Planning with language models through the lens of efficiency

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:43.512263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4fd5f7a6-11e6-45f4-b9d2-1a1f8a37b1d1 · outbound

This paper cites Pushing the envelope: Planning, propositional logic, and stochastic search.

Make Planning Research Rigorous Again! Pushing the envelope: Planning, propositional logic, and stochastic search

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:43.339674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0f9a0e1d-441e-4cb0-a3f4-ef6db580a635 · outbound

This paper cites Soft goals can be compiled away.Journal of Artificial Intelligence Research, 36:547–556, 2009.

Make Planning Research Rigorous Again! Soft goals can be compiled away.Journal of Artificial Intelligence Research, 36:547–556, 2009

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:43.217739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d72ce042-0e38-48b1-9cf1-93d8a85fefd6 · outbound

This paper cites ACPBench: Reasoning about action, change, and planning.

Make Planning Research Rigorous Again! ACPBench: Reasoning about action, change, and planning

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:43.043588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3fdb6758-22ad-4c6c-999d-c7d28754e18d · outbound

This paper cites Nau, Elnatan Reisner, and Robert P.

Make Planning Research Rigorous Again! Nau, Elnatan Reisner, and Robert P

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:42.904107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation bbbafe7b-8ed2-4aef-ba8f-5bd5f7afcf15 · outbound

This paper cites Beyond a ∗: Better planning with transformers via search dynamics bootstrapping.

Make Planning Research Rigorous Again! Beyond a ∗: Better planning with transformers via search dynamics bootstrapping

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:42.719460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 85153633-71cd-44a9-8f4d-20656b140c7e · outbound

This paper cites The deterministic part of the seventh international planning competition.Artificial Intelligence, 223:82–119, 2015.

Make Planning Research Rigorous Again! The deterministic part of the seventh international planning competition.Artificial Intelligence, 223:82–119, 2015

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:42.581052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 977cac94-e426-41ea-8dfc-75d1d79ee0c4 · outbound

This paper cites Width and serialization of classical planning problems.

Make Planning Research Rigorous Again! Width and serialization of classical planning problems

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:42.443069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation acb94c59-3a09-4d8e-80a1-0a260812a1bf · outbound

This paper cites an unresolved cited work.

Make Planning Research Rigorous Again! Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:32:42.326776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4824b6e4-386d-41ca-a3ae-3efc9fc7374f · outbound

This paper cites LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.

Make Planning Research Rigorous Again! LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:31.055187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6497273a-82e0-4684-b0cb-315d5d1ab8ee · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

Make Planning Research Rigorous Again! AgentBench: Evaluating LLMs as Agents

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:31.075094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22ab6745-4046-412c-89f9-9229be7a8838 · outbound

This paper cites Exploiting a graphplan framework in temporal planning.

Make Planning Research Rigorous Again! Exploiting a graphplan framework in temporal planning

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:42.197002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 90cd7094-4708-43e0-b013-0c0565cf441d · outbound

This paper cites Anderson, Daniel S.

Make Planning Research Rigorous Again! Anderson, Daniel S

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:42.037973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cc77b2fa-126e-4303-a006-06c4d0ce0a8d · outbound

This paper cites Sudoku as a sat problem.

Make Planning Research Rigorous Again! Sudoku as a sat problem

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:31.186034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78642a46-cfb1-4bda-b33f-2afb0c9e06cf · outbound

This paper cites AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents.

Make Planning Research Rigorous Again! AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:31.241598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a574e5e3-428c-4a80-b063-c0344c44cf2f · outbound

This paper cites Tenenbaum, and Leslie Pack Kaelbing.

Make Planning Research Rigorous Again! Tenenbaum, and Leslie Pack Kaelbing

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:41.830962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8a760062-476d-4f70-90f3-790fb1e39c2c · outbound

This paper cites Pattern database heuristics for fully observable nondeterministic planning.

Make Planning Research Rigorous Again! Pattern database heuristics for fully observable nondeterministic planning

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:41.668965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b48aeffa-8760-4096-aa95-69df8f515caf · outbound

This paper cites Synthesis Lectures on Artificial Intelligence and Machine Learning.

Make Planning Research Rigorous Again! Synthesis Lectures on Artificial Intelligence and Machine Learning

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:41.505624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 45ca76ef-f152-4e98-9b1d-c1ee5c5b411e · outbound

This paper cites PDDL – The Planning Domain Definition Language – Version 1.2.

Make Planning Research Rigorous Again! PDDL – The Planning Domain Definition Language – Version 1.2

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:41.418366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 52ae54ae-2c9c-4987-8062-c39bf3a8d9e5 · outbound

This paper cites Planning.Domains.

Make Planning Research Rigorous Again! Planning.Domains

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:41.265072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1f20170-a434-417d-8d2d-3d3a0e9d704a · outbound

This paper cites Planutils: Bringing planning to the masses.

Make Planning Research Rigorous Again! Planutils: Bringing planning to the masses

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:41.008357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d730b6f1-ba2e-4844-b9f8-0a029a58b342 · outbound

This paper cites Muise, Sheila A.

Make Planning Research Rigorous Again! Muise, Sheila A

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:40.923853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4fb8bfbf-560c-413a-8149-8ee713fd4b39 · outbound

This paper cites Muise, Sheila A.

Make Planning Research Rigorous Again! Muise, Sheila A

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:40.711642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 14b4ff11-8f32-471f-8aad-1f8d17edb136 · outbound

This paper cites Nau, Tsz-Chiu Au, Okhtay Ilghami, Ugur Kuter, J.

Make Planning Research Rigorous Again! Nau, Tsz-Chiu Au, Okhtay Ilghami, Ugur Kuter, J

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:31.930187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14f545ea-0dd6-4dd8-985f-a98d602521ec · outbound

This paper cites Large language models as planning domain generators.

Make Planning Research Rigorous Again! Large language models as planning domain generators

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:40.552468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d0d8101c-2321-4c14-a487-cdd5f8997f66 · outbound

This paper cites Compiling uncertainty away in conformant planning problems with bounded width.Journal of Artificial Intelligence Research, 35:623–675, 2009.

Make Planning Research Rigorous Again! Compiling uncertainty away in conformant planning problems with bounded width.Journal of Artificial Intelligence Research, 35:623–675, 2009

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:40.380875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 32ea7410-4352-4e01-a8d0-d0e2e71c8da6 · outbound

This paper cites Planning with numeric timed initial fluents.

Make Planning Research Rigorous Again! Planning with numeric timed initial fluents

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:40.182754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4af91f66-89d5-49f2-ac26-fb0f75430ad7 · outbound

This paper cites Rosenschein.

Make Planning Research Rigorous Again! Rosenschein

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:40.009784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 51197954-c96b-4662-a749-6a955d672187 · outbound

This paper cites MIT Press, 2001.

Make Planning Research Rigorous Again! MIT Press, 2001

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:32.267967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f4ed307-70b5-4fa0-bdac-6064b858ab26 · outbound

This paper cites System 1.x: Learning to balance fast and slow planning with language models.

Make Planning Research Rigorous Again! System 1.x: Learning to balance fast and slow planning with language models

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:39.815832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e45375cb-8d80-4df1-96db-ed573f3fe98a · outbound

This paper cites Relational dynamic influence diagram language (RDDL): Language description, 2010.

Make Planning Research Rigorous Again! Relational dynamic influence diagram language (RDDL): Language description, 2010

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:39.652973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dcd8d5be-7c6c-449d-a680-85cd8dee413d · outbound

This paper cites PDDL generators.

Make Planning Research Rigorous Again! PDDL generators

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:32.525740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b71bad0-7113-475d-9baa-4fc12edc5231 · outbound

This paper cites Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models.

Make Planning Research Rigorous Again! Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T13:32:32.584449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9db5074-80f2-4446-9052-1bf48522d53d · outbound

This paper cites Alfworld: Aligning text and embodied environments for interactive learning.

Make Planning Research Rigorous Again! Alfworld: Aligning text and embodied environments for interactive learning

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:39.525356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e4f853c6-7ba4-40cb-bc49-1f6d96a9b29a · outbound

This paper cites Generalized planning in PDDL domains with pretrained large language mod- els.

Make Planning Research Rigorous Again! Generalized planning in PDDL domains with pretrained large language mod- els

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:39.328344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e1305527-b57d-44cd-ac57-6106970337ee · outbound

This paper cites Sudoku as a constraint problem.

Make Planning Research Rigorous Again! Sudoku as a constraint problem

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:39.167334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 623c2ded-c44d-4b53-ba50-052aec7e97f3 · outbound

This paper cites The complexity of propositional linear temporal logics.Journal of the ACM, 32(3):733–749, 1985.

Make Planning Research Rigorous Again! The complexity of propositional linear temporal logics.Journal of the ACM, 32(3):733–749, 1985

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:32:38.972402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers