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Paper Citation Record · LEDGER

Meta-learning how to Share Credit among Macro-Actions

As of 16 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.13690.

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

pith.paper-citation-record.v1
2506.13690 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:33:25.016687Z

measured 39 of 39 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved17
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c032ebbc-9c2e-46ee-a361-fe1d88d5b00b · outbound

This paper cites Mas- tering the game of go with deep neural networks and tree search.

Meta-learning how to Share Credit among Macro-Actions Mas- tering the game of go with deep neural networks and tree search

Reference 1

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unresolved
no resolver link, observed 2026-08-07T00:33:24.784818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.784818Z digest=sha256:cf9e349fcff18bc02dfddf228db2a1e6de46a339ac2d7fd4130ff570e5052e4a

Observation 5293bb1b-0cb6-4997-8349-c0e0c202749c · outbound

This paper cites Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H.

Meta-learning how to Share Credit among Macro-Actions Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H

Reference 2

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unresolved
no resolver link, observed 2026-08-07T00:33:24.815439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.815439Z digest=sha256:2a3206e42d8144b875c387d5d190b2849459514d24e53962c27a7687309c252c

Observation efaa988e-376d-495e-b48f-edcb56b3070a · outbound

This paper cites Dota 2 with Large Scale Deep Reinforcement Learning.

Meta-learning how to Share Credit among Macro-Actions Dota 2 with Large Scale Deep Reinforcement Learning

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.820678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.820678Z digest=sha256:ef0b206a1bce681e0f0e530e35b68485e8df42a55a727a22c7d47eaabbd0c4fc

Observation 1550dea7-2e6d-4b8a-8c3e-723b6dcf7f3e · outbound

This paper cites Autonomous navigation of stratospheric balloons using reinforcement learning.

Meta-learning how to Share Credit among Macro-Actions Autonomous navigation of stratospheric balloons using reinforcement learning

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:28.860074Z

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.

source=pdf_text observed=2026-08-07T00:33:24.824827Z digest=sha256:97fc34d05e68636bcfc52701819007160da4696e7f61f07a153c8046a29c2a20

Observation e134d38b-7f0c-48d9-8251-0e86ca64c058 · outbound

This paper cites Magnetic control of tokamak plasmas through deep reinforcement learning.

Meta-learning how to Share Credit among Macro-Actions Magnetic control of tokamak plasmas through deep reinforcement learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:28.618915Z

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.

source=pdf_text observed=2026-08-07T00:33:24.834321Z digest=sha256:2a4fcab0de5997166779ef6d0a84217f15bcd55d7c02c1dd264c967c16f96afe

Observation b97099db-f115-465c-869a-d62877af7863 · outbound

This paper cites an unresolved cited work.

Meta-learning how to Share Credit among Macro-Actions Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:33:28.416804Z

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.

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Observation 89f20de9-1747-46ab-b6b9-641b87c887f6 · outbound

This paper cites Hierarchical solution of markov decision processes using macro-actions.

Meta-learning how to Share Credit among Macro-Actions Hierarchical solution of markov decision processes using macro-actions

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:28.120610Z

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.

source=pdf_text observed=2026-08-07T00:33:24.847801Z digest=sha256:5ebfc9852d21b99f9673a0344003364134f828d0226ea47da6872b550e99cf05

Observation d911cf51-915f-40ee-a8f0-d1eec8604439 · outbound

This paper cites Fikes and Nils J.

Meta-learning how to Share Credit among Macro-Actions Fikes and Nils J

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.851769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.851769Z digest=sha256:2f21f22e030dd40c0d3c3cb7177cf0cf6e1aee732194b1d206b8c2fb398d1a7a

Observation 6d934cc5-c425-4162-9b9f-d21b743f5ae3 · outbound

This paper cites an unresolved cited work.

Meta-learning how to Share Credit among Macro-Actions Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:33:28.020322Z

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.

source=pdf_text observed=2026-08-07T00:33:24.855868Z digest=sha256:7f35e2afeac77a2e639cc73b88d9b5354b655732ad04b9dcb8e2ffdab78e0e0d

Observation 10a3d0ce-5480-461f-abac-770f3db7d5b3 · outbound

This paper cites Durugkar, Clemens Rosenbaum, Stefan Dernbach, and Sridhar Mahadevan.

Meta-learning how to Share Credit among Macro-Actions Durugkar, Clemens Rosenbaum, Stefan Dernbach, and Sridhar Mahadevan

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:27.845972Z

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.

source=pdf_text observed=2026-08-07T00:33:24.859868Z digest=sha256:4db367a8846d97f2834dbe9ae592e3a9ed8507f21fd8205cd7bdb137d04eba7e

Observation bd294195-f6c9-4baa-9985-dd1a27100afa · outbound

This paper cites Rainbow: Combining improve- ments in deep reinforcement learning.

Meta-learning how to Share Credit among Macro-Actions Rainbow: Combining improve- ments in deep reinforcement learning

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:27.642436Z

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.

source=pdf_text observed=2026-08-07T00:33:24.863690Z digest=sha256:6e3034fbdeadf11eaf09ce1f05ca72d91e41a7c55524ffc0edc07e7d1f6858fc

Observation 43c626f0-e847-4ef6-b22b-87cd80632f26 · outbound

This paper cites Learning macro-actions in reinforcement learning.

Meta-learning how to Share Credit among Macro-Actions Learning macro-actions in reinforcement learning

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:27.346950Z

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.

source=pdf_text observed=2026-08-07T00:33:24.867588Z digest=sha256:4c28d4ec06c8861e07b38c039d6d726fe0e64bbc5368d6c15f9624161f8fceaa

Observation f83086f3-342b-4f35-96e1-961be60390b2 · outbound

This paper cites Macro-actions in reinforcement learning: An empirical analysis.

Meta-learning how to Share Credit among Macro-Actions Macro-actions in reinforcement learning: An empirical analysis

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:27.134155Z

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.

source=pdf_text observed=2026-08-07T00:33:24.871801Z digest=sha256:034a8a6fea9100ec8c16758e35785f984a81904c1cbe96a7e14e62a6926c2d5d

Observation aff8175a-875f-48c2-adaf-321be739ae24 · outbound

This paper cites Meta learning shared hierarchies.

Meta-learning how to Share Credit among Macro-Actions Meta learning shared hierarchies

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:26.896757Z

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.

source=pdf_text observed=2026-08-07T00:33:24.876353Z digest=sha256:115090a16a3afc583333e073bbe59fe59bbc72a496edf1c02a4f1e63986799cb

Observation e1bf3579-d282-4194-b486-5fac2345c4ce · outbound

This paper cites Hierarchical Meta-Reinforcement Learning via Automated Macro-Action Discovery.

Meta-learning how to Share Credit among Macro-Actions Hierarchical Meta-Reinforcement Learning via Automated Macro-Action Discovery

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.881222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.881222Z digest=sha256:ac80946b760cc95519fe3dac1b4ef8f14d75d2018aa2963b2bf189027b8436b5

Observation dacd4186-125f-479b-aaf4-cf4c4eaf1a89 · outbound

This paper cites Deep reinforcement learning for decentralized multi-robot exploration with macro actions.

Meta-learning how to Share Credit among Macro-Actions Deep reinforcement learning for decentralized multi-robot exploration with macro actions

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:26.767158Z

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.

source=pdf_text observed=2026-08-07T00:33:24.885488Z digest=sha256:e0a5ae47cbc163397008a0219486d7ab26f05268c2b0d446ff4cbd1ff8f09cc7

Observation 70379299-e73c-4cc0-9a69-730e3e2b758f · outbound

This paper cites Macro-Action-Based Multi-Agent/Robot Deep Reinforcement Learning under Partial Observability.

Meta-learning how to Share Credit among Macro-Actions Macro-Action-Based Multi-Agent/Robot Deep Reinforcement Learning under Partial Observability

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:26.537499Z

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.

source=pdf_text observed=2026-08-07T00:33:24.890230Z digest=sha256:840d47c4f89ee570761423c46b45635e8005bca13cfe5d73c66f3531702a0f69

Observation cd121df8-6703-47da-97dd-62af7a387c5c · outbound

This paper cites Unlocking new strategies: Intrinsic exploration for evolving macro and micro actions.

Meta-learning how to Share Credit among Macro-Actions Unlocking new strategies: Intrinsic exploration for evolving macro and micro actions

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:26.359326Z

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.

source=pdf_text observed=2026-08-07T00:33:24.893857Z digest=sha256:47771aa87cd199db495325d64fed6c782408955d54d7eac33427f9f763138cea

Observation 08dc6753-272d-4a80-9ee9-df5b85750ee3 · outbound

This paper cites Reusability and Transferability of Macro Actions for Reinforcement Learning.

Meta-learning how to Share Credit among Macro-Actions Reusability and Transferability of Macro Actions for Reinforcement Learning

Reference 19

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T00:33:25.228396Z

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.

source=pdf_text observed=2026-08-07T00:33:24.897577Z digest=sha256:7a358efa061b2c81eb06104ab01e3ede960363c202884e4128f58f8fe8705a79

Observation ebba5e75-b913-477f-9a69-37e3efbe2511 · outbound

This paper cites Efficient Black-Box Planning Using Macro-Actions with Focused Effects.

Meta-learning how to Share Credit among Macro-Actions Efficient Black-Box Planning Using Macro-Actions with Focused Effects

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:33:25.197756Z

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.

source=pdf_text observed=2026-08-07T00:33:24.901782Z digest=sha256:5dfe93687a83b74f923e4735632ec1a6d8b255d65ddf96f86d451f45cf467372

Observation fa82daaf-83d0-41d2-a3f4-192602222500 · outbound

This paper cites Learning macro-actions for arbitrary planners and domains.

Meta-learning how to Share Credit among Macro-Actions Learning macro-actions for arbitrary planners and domains

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:26.275840Z

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.

source=pdf_text observed=2026-08-07T00:33:24.906030Z digest=sha256:fd8588a41aa4a7ae713e66ec8eddfce9479ad17867d0efbeef690918781837f7

Observation e5866fb1-179f-47e0-9711-492435eb9a86 · outbound

This paper cites Modeling and planning with macro-actions in decentralized pomdps.

Meta-learning how to Share Credit among Macro-Actions Modeling and planning with macro-actions in decentralized pomdps

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:26.202469Z

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.

source=pdf_text observed=2026-08-07T00:33:24.909481Z digest=sha256:afad7dd4d54deaff35b0210491d34416693f37fbb52b8b29a7c1dce828759b63

Observation 33e48015-0851-484f-b36e-d3619ed0a3b5 · outbound

This paper cites MAGIC: Learning Macro-Actions for Online POMDP Planning.

Meta-learning how to Share Credit among Macro-Actions MAGIC: Learning Macro-Actions for Online POMDP Planning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.917700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.917700Z digest=sha256:d3bf10c198401c78158b00699cc4e819d7a6366db38e15fcd3f551915d4f99b1

Observation d8b605d1-db0b-4be6-8d9c-0fecf3c76f89 · outbound

This paper cites Deep Reinforcement Learning Based Navigation with Macro Actions and Topological Maps.

Meta-learning how to Share Credit among Macro-Actions Deep Reinforcement Learning Based Navigation with Macro Actions and Topological Maps

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.924438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.924438Z digest=sha256:d51a38af24709fd086fd355d3f34a0aa60a7b660463ed1d62b1c2f082edb64e9

Observation 7b78c45f-3d47-4264-aa80-9701fb320388 · outbound

This paper cites Human-level control through deep reinforcement learning.

Meta-learning how to Share Credit among Macro-Actions Human-level control through deep reinforcement learning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.928615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.928615Z digest=sha256:4359115151d43140eb9e9b4408e098106c7d8db1f5ac8e6e658907d403678774

Observation 2dd9f7fc-0919-41ec-8840-80b3e8c53152 · outbound

This paper cites Bellemare, Will Dabney, and Rémi Munos.

Meta-learning how to Share Credit among Macro-Actions Bellemare, Will Dabney, and Rémi Munos

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:26.074752Z

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.

source=pdf_text observed=2026-08-07T00:33:24.932262Z digest=sha256:5ce82fd781b8cf921d4ae563ff95a29bc1312f5bfee09b7605857f2fcf7d54cc

Observation 3938a167-c961-4f21-bd21-b3c6b175e0e0 · outbound

This paper cites an unresolved cited work.

Meta-learning how to Share Credit among Macro-Actions Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-07T00:33:25.914748Z

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.

source=pdf_text observed=2026-08-07T00:33:24.936341Z digest=sha256:b7b841ba47d6baa2101af6fa552400e7b52645d2a13f00aa89d1f702267884dd

Observation e52ef023-d402-4c67-9239-969339b33889 · outbound

This paper cites Prioritized Experience Replay.

Meta-learning how to Share Credit among Macro-Actions Prioritized Experience Replay

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.940102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.940102Z digest=sha256:86a9704127b1d9aa9f6c0b39a616db7e72ad746bb6717a0792e99e586aeb1035

Observation 23c92e8c-3033-433a-b610-33cdbee5ce27 · outbound

This paper cites Deep reinforcement learning with double q-learning.

Meta-learning how to Share Credit among Macro-Actions Deep reinforcement learning with double q-learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.944182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.944182Z digest=sha256:4a65e7155aa243c469c67de4ce17967e0c5b729941f0d13054be94b283eaf900

Observation 32133ac0-1f1e-44bb-ac77-14e07dfc6df8 · outbound

This paper cites Dueling network architectures for deep reinforcement learning.

Meta-learning how to Share Credit among Macro-Actions Dueling network architectures for deep reinforcement learning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.948639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.948639Z digest=sha256:a7fb92edba84e9595a4cd71125fd78828fa52836bdbf174f7132296026488f55

Observation da0d07e9-62a7-43c6-8d8d-cbae40b1b60c · outbound

This paper cites Noisy Networks for Exploration.

Meta-learning how to Share Credit among Macro-Actions Noisy Networks for Exploration

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.952368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.952368Z digest=sha256:f3c50674f4d63ae3d795a22b2e582b5e47764821bd1ae9b13a37415b103d3033

Observation 783e554d-9d9f-441d-8ac5-76e368f69599 · outbound

This paper cites Meta-gradient reinforcement learning.

Meta-learning how to Share Credit among Macro-Actions Meta-gradient reinforcement learning

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:25.665399Z

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.

source=pdf_text observed=2026-08-07T00:33:24.956996Z digest=sha256:2493050f717f53f8bebd688032afde5fd133643efc70fce87be1dc151c74ac0e

Observation 73968742-7555-49a2-9de1-b2ba74f34a83 · outbound

This paper cites Universal value function approxima- tors.

Meta-learning how to Share Credit among Macro-Actions Universal value function approxima- tors

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:25.559712Z

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.

source=pdf_text observed=2026-08-07T00:33:24.967341Z digest=sha256:3e62e7e024b576d691bf8e5b341633bb6b4ea7fde96a5271d3c11eff16b95bfd

Observation 288709fa-0c4b-49f7-b2d3-d811e4c5cf4f · outbound

This paper cites The arcade learning environment: An evaluation platform for general agents.

Meta-learning how to Share Credit among Macro-Actions The arcade learning environment: An evaluation platform for general agents

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.972757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.972757Z digest=sha256:eb4b4612eeaad012266bf42e11c96c63490de759ac36f5689c0d4082e4897209

Observation a756d7de-1916-4c1b-a497-9b7424264729 · outbound

This paper cites OpenAI Gym.

Meta-learning how to Share Credit among Macro-Actions OpenAI Gym

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T00:33:24.980907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:33:24.980907Z digest=sha256:0e1dc2765234dcaae6958bd39d3d50f79a26262b6fdd77c98d867f58a16a32f0

Observation 4a619404-64c9-49f3-990e-b2e22582241b · outbound

This paper cites The Atari Grand Challenge Dataset.

Meta-learning how to Share Credit among Macro-Actions The Atari Grand Challenge Dataset

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:33:25.057740Z

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.

source=pdf_text observed=2026-08-07T00:33:24.996820Z digest=sha256:79c6831a8dedc9ab2152b024ddafd62ace331184f4d851fe15eeb4bc2be0f09c

Observation 75bbc518-cc62-4693-b51f-183392014552 · outbound

This paper cites Gym-minigrid: Minimalistic gridworld environment for openai gym.

Meta-learning how to Share Credit among Macro-Actions Gym-minigrid: Minimalistic gridworld environment for openai gym

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:25.504282Z

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.

source=pdf_text observed=2026-08-07T00:33:25.001724Z digest=sha256:2bc3b30d07fa6da32dc93730ec3934471e1800ba2712ec80d7b4d5f6a10440be

Observation bfe23e56-c531-443b-a03e-b43f469d379a · outbound

This paper cites - Perform a standard TD update with the MASP penalty, updating θ → θ′ using Σ fixed.

Meta-learning how to Share Credit among Macro-Actions - Perform a standard TD update with the MASP penalty, updating θ → θ′ using Σ fixed

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:33:25.489509Z

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.

source=pdf_text observed=2026-08-07T00:33:25.005793Z digest=sha256:9ef89a1db843f7f3342e8f0dd5d9b8fa867df745edff389bbf6ef189096dfdc5

Observation e3f33879-12df-4e55-8281-c15b9750d088 · outbound

This paper cites - Evaluate the performance of the updated θ′ using a meta-objective (the standard TD loss).

Meta-learning how to Share Credit among Macro-Actions - Evaluate the performance of the updated θ′ using a meta-objective (the standard TD loss)

Reference 39

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T00:33:25.449892Z

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.

source=pdf_text observed=2026-08-07T00:33:25.016687Z digest=sha256:65ff60bc528255eeadbaf099f35741afd803ea7ce1afb2fc6810327f7881f110

Pith citing papers

No inbound Pith citation observations are available.