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Paper Citation Record · LEDGER

Calculating Mutual Information between a Reward Maximizer and its Environment

As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2602.12963.

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

pith.paper-citation-record.v1
2602.12963 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:49:13.596563Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

19 of 19 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e3fe48a-588d-47b7-ab43-4d14e62e5a2d · outbound

This paper cites Un- derstanding world or predicting future? a comprehensive survey of world models.ACM Computing Surveys, 58(3):1–38, 2025.

Calculating Mutual Information between a Reward Maximizer and its Environment Un- derstanding world or predicting future? a comprehensive survey of world models.ACM Computing Surveys, 58(3):1–38, 2025

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 8a3652af-c5ab-4b61-a99b-fa0245389e3c · outbound

This paper cites Towards a formalization of the agent structure problem.

Calculating Mutual Information between a Reward Maximizer and its Environment Towards a formalization of the agent structure problem

Reference 2

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source=pdf_text observed=2026-08-02T23:49:11.258549Z digest=sha256:e3766a78e718df51c3fa9feb275f2a185309f8661b4838d54e638237ffaf68a4

Observation e41e4456-b722-4f07-98c0-328c269f6bc3 · outbound

This paper cites General agents need world models.

Calculating Mutual Information between a Reward Maximizer and its Environment General agents need world models

Reference 3

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source=pdf_text observed=2026-08-02T23:49:11.439453Z digest=sha256:c7de8cf13c55b9ba4b1a3d36cd8f958129efabe950f1f723ef1e3ebf83caa0d9

Observation 07ab1773-502a-49db-82df-e7abcdd5fdc6 · outbound

This paper cites Settling the reward hypothesis.

Calculating Mutual Information between a Reward Maximizer and its Environment Settling the reward hypothesis

Reference 4

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source=pdf_text observed=2026-08-02T23:49:11.562592Z digest=sha256:77418d613cbe24331b85dab1235f84956e7acc44c599eb895765e7d3c8222a94

Observation a8ca5bdb-a5f8-4b1d-b733-3e072f9b219f · outbound

This paper cites Theory of games and economic behavior: 60th anniversary commemorative edition.

Calculating Mutual Information between a Reward Maximizer and its Environment Theory of games and economic behavior: 60th anniversary commemorative edition

Reference 5

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source=pdf_text observed=2026-08-02T23:49:11.739683Z digest=sha256:71748c3aff715a14b29034fe8520258a36ba692aed8f7424d9b45a06f3366d27

Observation d393cda6-21de-41cd-b691-663d49d15f39 · outbound

This paper cites Sutton and Andrew G.

Calculating Mutual Information between a Reward Maximizer and its Environment Sutton and Andrew G

Reference 6

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source=pdf_text observed=2026-08-02T23:49:11.863297Z digest=sha256:b5aeb94a78dc1aac198eb323108478124aa6f0cc2d786abea7a203a56a3c9e4d

Observation 3c86aaf1-d795-4000-8da6-0eef4a566a38 · outbound

This paper cites Intelligence without representation.Artificial intelli- gence, 47(1-3):139–159, 1991.

Calculating Mutual Information between a Reward Maximizer and its Environment Intelligence without representation.Artificial intelli- gence, 47(1-3):139–159, 1991

Reference 7

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source=pdf_text observed=2026-08-02T23:49:12.049213Z digest=sha256:6da67375066117d57a40627fbaa0b8ea1c20bd96d13555e891c196e39927e643

Observation 4dd0cab2-65ce-451b-8acd-d9d533e87d7e · outbound

This paper cites The bitter lesson.Incomplete Ideas (blog), 13(1):38, 2019.

Calculating Mutual Information between a Reward Maximizer and its Environment The bitter lesson.Incomplete Ideas (blog), 13(1):38, 2019

Reference 8

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source=pdf_text observed=2026-08-02T23:49:12.201047Z digest=sha256:890b9c38bb3ffc0f69c3d7137ba17c25be48214df6f35148b24521a3eebaa093

Observation 4398e965-cbfc-46bc-bf11-d5167ddae59a · outbound

This paper cites World Models.

Calculating Mutual Information between a Reward Maximizer and its Environment World Models

Reference 9

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source=pdf_text observed=2026-08-02T23:49:12.322309Z digest=sha256:486bfc3b721c33c06ee38a22bd675efd8a9f753e9f0c2c1a4b65472c989ff4f9

Observation fe8f54fc-3bc4-4a36-83e0-4a9f88966cb7 · outbound

This paper cites Information-theoretic approach to the study of control systems.Physica A: Statistical Mechanics and its Appli- cations, 331(1-2):140–172, 2004.

Calculating Mutual Information between a Reward Maximizer and its Environment Information-theoretic approach to the study of control systems.Physica A: Statistical Mechanics and its Appli- cations, 331(1-2):140–172, 2004

Reference 10

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Observation 584c8a66-b773-4203-a89d-1a8991ffc0be · outbound

This paper cites Robust agents learn causal world models.

Calculating Mutual Information between a Reward Maximizer and its Environment Robust agents learn causal world models

Reference 11

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Observation b7128e84-2c7e-4286-8d94-c69f5b10ea6a · outbound

This paper cites General agents contain world models, even under par- tial observability and stochasticity.arXiv preprint arXiv:2602.03146, 2026.

Calculating Mutual Information between a Reward Maximizer and its Environment General agents contain world models, even under par- tial observability and stochasticity.arXiv preprint arXiv:2602.03146, 2026

Reference 12

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source=pdf_text observed=2026-08-02T23:49:12.717620Z digest=sha256:e8f46579871bb7bcf108f39c76331190a8ac54ea819caa1f42514f7115fbdecf

Observation bc28576c-5617-451c-a329-2048f28c2a6a · outbound

This paper cites John Wiley & Sons, 1999.

Calculating Mutual Information between a Reward Maximizer and its Environment John Wiley & Sons, 1999

Reference 13

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source=pdf_text observed=2026-08-02T23:49:12.832985Z digest=sha256:51b9a36e02a1b86cbf1f1b8d4a0ad542f0ab6f071ac8cb10af58de5d1cff1ce1

Observation 519a8eae-4d91-4e25-be99-7a18e303b21a · outbound

This paper cites The Zero Set of a Real Analytic Function.

Calculating Mutual Information between a Reward Maximizer and its Environment The Zero Set of a Real Analytic Function

Reference 14

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Observation 281b0e34-4bc1-43ab-880d-ae7425e459c3 · outbound

This paper cites Spivak.Calculus On Manifolds: A Modern Approach To Classical The- orems Of Advanced Calculus (1st ed.).

Calculating Mutual Information between a Reward Maximizer and its Environment Spivak.Calculus On Manifolds: A Modern Approach To Classical The- orems Of Advanced Calculus (1st ed.)

Reference 15

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source=pdf_text observed=2026-08-02T23:49:13.125841Z digest=sha256:239559c829e708aabb14bc2fc935a69867b219550bd8cf15308208c09c41c07b

Observation f9bd66fc-3985-40c4-ac07-357cd25ef09f · outbound

This paper cites Number 2.

Calculating Mutual Information between a Reward Maximizer and its Environment Number 2

Reference 16

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source=pdf_text observed=2026-08-02T23:49:13.273065Z digest=sha256:14fe09240eec280dae77a0e2cf94e6f5f3049c6c69362f9144482855577b6d13

Observation 52126812-be58-4599-a0d5-aa32a1f89244 · outbound

This paper cites an unresolved cited work.

Calculating Mutual Information between a Reward Maximizer and its Environment Unresolved cited work

Reference 17

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source=pdf_text observed=2026-08-02T23:49:13.412807Z digest=sha256:a89cc7d97096a16400823d7d2b94da7d290f06690b40a69c6b4b9e6b8e749063

Observation 9ac7b669-87d7-41bc-b065-246ed2f1bb7e · outbound

This paper cites Courier Corporation, 2012.

Calculating Mutual Information between a Reward Maximizer and its Environment Courier Corporation, 2012

Reference 18

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source=pdf_text observed=2026-08-02T23:49:13.596563Z digest=sha256:134ed1310ffb3a594383fac8b6aaf2b57943158f5cd95febec01f92940ea58a1

Observation 22eef67d-ca49-464c-9f1a-440385ca21ef · outbound

This paper cites an unresolved cited work.

Calculating Mutual Information between a Reward Maximizer and its Environment Unresolved cited work

Reference 107

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source=pdf_text observed=2026-08-02T23:49:13.495204Z digest=sha256:868b2be9fc865efb625a99680b1a51cb2e6f924eecca4fd0f71f771eb8599a49

Pith citing papers

No inbound Pith citation observations are available.