Provably Optimal Learning Algorithms for Assistance Games | Paper Citation Record

Observation bf57c6c5-f56e-46dc-baf0-ef98ee61337c · outbound

This paper cites Improved differentially private and lazy online convex optimization: Lower regret without smoothness requirements.

Provably Optimal Learning Algorithms for Assistance Games Improved differentially private and lazy online convex optimization: Lower regret without smoothness requirements

Reference 1

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This paper cites Online learning over a finite action set with limited switching.

Provably Optimal Learning Algorithms for Assistance Games Online learning over a finite action set with limited switching

Reference 2

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This paper cites Human expertise in algorithmic prediction.

Provably Optimal Learning Algorithms for Assistance Games Human expertise in algorithmic prediction

Reference 3

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This paper cites Online learning for adversaries with memory: price of past mistakes.

Provably Optimal Learning Algorithms for Assistance Games Online learning for adversaries with memory: price of past mistakes

Reference 4

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This paper cites The allocation of decision authority to human and artificial intelligence.

Provably Optimal Learning Algorithms for Assistance Games The allocation of decision authority to human and artificial intelligence

Reference 5

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This paper cites Does the whole exceed its parts? the effect of ai explanations on complementary team performance.

Provably Optimal Learning Algorithms for Assistance Games Does the whole exceed its parts? the effect of ai explanations on complementary team performance

Reference 6

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Observation c7eba8c3-5824-4195-8fa4-0e3f960b4793 · outbound

This paper cites Is learning in games good for the learners? Advances in Neural Information Processing Systems, 36, 2024.

Provably Optimal Learning Algorithms for Assistance Games Is learning in games good for the learners? Advances in Neural Information Processing Systems, 36, 2024

Reference 7

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This paper cites Mirror descent meets fixed share (and feels no regret).

Provably Optimal Learning Algorithms for Assistance Games Mirror descent meets fixed share (and feels no regret)

Reference 8

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Observation 9d67f9cc-edb3-46c8-943a-6a08622e5022 · outbound

This paper cites Emergent communication at scale.

Provably Optimal Learning Algorithms for Assistance Games Emergent communication at scale

Reference 9

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This paper cites Dependent randomized rounding via exchange properties of combinatorial structures.

Provably Optimal Learning Algorithms for Assistance Games Dependent randomized rounding via exchange properties of combinatorial structures

Reference 10

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This paper cites On the np-completeness of finding an optimal strategy in games with common payoffs.

Provably Optimal Learning Algorithms for Assistance Games On the np-completeness of finding an optimal strategy in games with common payoffs

Reference 11

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Observation d8aa3727-bcf9-485b-bd4c-d53e80cec3a2 · outbound

This paper cites Collaborative prediction: Tractable information aggregation via agreement.

Provably Optimal Learning Algorithms for Assistance Games Collaborative prediction: Tractable information aggregation via agreement

Reference 12

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This paper cites Computing the optimal strategy to commit to.

Provably Optimal Learning Algorithms for Assistance Games Computing the optimal strategy to commit to

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.941024Z

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Observation 0f8fd976-3091-47ec-82d6-94b2dfb9d8fc · outbound

This paper cites Strongly adaptive online learning.

Provably Optimal Learning Algorithms for Assistance Games Strongly adaptive online learning

Reference 14

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Observation 32d0adf9-af4d-415f-b910-54b4e8eb75c4 · outbound

This paper cites Human-algorithm collaboration: Achieving complementarity and avoiding unfairness.

Provably Optimal Learning Algorithms for Assistance Games Human-algorithm collaboration: Achieving complementarity and avoiding unfairness

Reference 15

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This paper cites A threshold of ln n for approximating set cover.

Provably Optimal Learning Algorithms for Assistance Games A threshold of ln n for approximating set cover

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.975018Z

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Observation 9ed5cea4-32b1-43d4-a32e-3bb98e87b57a · outbound

This paper cites A decision-theoretic model of assistance.

Provably Optimal Learning Algorithms for Assistance Games A decision-theoretic model of assistance

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.953811Z

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Observation 5bf1adff-5cc1-4763-9807-51157cea4c68 · outbound

This paper cites Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks.

Provably Optimal Learning Algorithms for Assistance Games Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks

Reference 18

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This paper cites Interpretation of optimal signals.

Provably Optimal Learning Algorithms for Assistance Games Interpretation of optimal signals

Reference 19

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Observation 8f29d5c4-98d1-45ff-9501-b1e8551fd92b · outbound

This paper cites Signal to act: Game theory in pragmatics.

Provably Optimal Learning Algorithms for Assistance Games Signal to act: Game theory in pragmatics

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.910041Z

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Observation 282c5dee-bb4e-4c07-b83c-4de7e27760f1 · outbound

This paper cites Nash and correlated equilibria: Some complexity considerations.

Provably Optimal Learning Algorithms for Assistance Games Nash and correlated equilibria: Some complexity considerations

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.936991Z

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This paper cites The principles and limits of algorithm-in-the-loop decision making.

Provably Optimal Learning Algorithms for Assistance Games The principles and limits of algorithm-in-the-loop decision making

Reference 22

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This paper cites Designing algorithmic delegates: The role of indistinguishability in human-ai handoff.

Provably Optimal Learning Algorithms for Assistance Games Designing algorithmic delegates: The role of indistinguishability in human-ai handoff

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.921940Z

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Observation 676bf65e-adb6-470e-895b-9921e1a265de · outbound

This paper cites Cooperative inverse reinforcement learning.

Provably Optimal Learning Algorithms for Assistance Games Cooperative inverse reinforcement learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.958762Z

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Observation 76b66119-62cf-4cb0-bbdb-5b01a6bc7a23 · outbound

This paper cites The off-switch game.

Provably Optimal Learning Algorithms for Assistance Games The off-switch game

Reference 25

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Observation 8f2e8279-f852-4b7d-95b7-10514d372c74 · outbound

This paper cites Emergence of language with multi-agent games: Learning to communicate with sequences of symbols.

Provably Optimal Learning Algorithms for Assistance Games Emergence of language with multi-agent games: Learning to communicate with sequences of symbols

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.955381Z

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Observation 47e77be0-eb46-4282-a6e8-bfa073eafc4f · outbound

This paper cites Adaptive algorithms for online decision problems.

Provably Optimal Learning Algorithms for Assistance Games Adaptive algorithms for online decision problems

Reference 27

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Observation a5114093-e081-436a-9430-2f1ac22e0c84 · outbound

This paper cites Tracking the best expert.

Provably Optimal Learning Algorithms for Assistance Games Tracking the best expert

Reference 28

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Observation dee198a2-f341-41ad-a8c2-b34e7b392b56 · outbound

This paper cites Team decision theory and information structures in optimal control problems--part i.

Provably Optimal Learning Algorithms for Assistance Games Team decision theory and information structures in optimal control problems--part i

Reference 29

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Observation 676438a4-bfaf-410e-8d6c-c8fdb16b33aa · outbound

This paper cites Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning.

Provably Optimal Learning Algorithms for Assistance Games Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning

Reference 30

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This paper cites Game dynamics connects semantics and pragmatics.

Provably Optimal Learning Algorithms for Assistance Games Game dynamics connects semantics and pragmatics

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.928735Z

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Observation b4415652-6186-4394-8402-973e1c4b4c17 · outbound

This paper cites Game theory in semantics and pragmatics.

Provably Optimal Learning Algorithms for Assistance Games Game theory in semantics and pragmatics

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.947403Z

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Observation 4f071f21-d9c1-48e7-85a1-9659846c78c5 · outbound

This paper cites Online submodular welfare maximization: Greedy is optimal.

Provably Optimal Learning Algorithms for Assistance Games Online submodular welfare maximization: Greedy is optimal

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.918163Z

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Observation 95e0472c-2ee3-4045-9f89-f6d6784763e3 · outbound

This paper cites Emergent communication under varying sizes and connectivities.

Provably Optimal Learning Algorithms for Assistance Games Emergent communication under varying sizes and connectivities

Reference 34

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Observation 4c2546cb-c9c9-4350-b4e2-5af766c2a88b · outbound

This paper cites Natural language from artificial life.

Provably Optimal Learning Algorithms for Assistance Games Natural language from artificial life

Reference 35

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Observation 03a877a7-6d71-47b1-bbba-04dd0bacd061 · outbound

This paper cites Iterated learning and the evolution of language.

Provably Optimal Learning Algorithms for Assistance Games Iterated learning and the evolution of language

Reference 36

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Observation 63fe05d7-971c-4a90-84f2-4cebe6dc99b6 · outbound

This paper cites Assistancezero: Scalably solving assistance games.

Provably Optimal Learning Algorithms for Assistance Games Assistancezero: Scalably solving assistance games

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.960645Z

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Observation eeed42ea-9491-41e7-bd7c-528e71fe7a3d · outbound

This paper cites Emergent Multi-Agent Communication in the Deep Learning Era.

Provably Optimal Learning Algorithms for Assistance Games Emergent Multi-Agent Communication in the Deep Learning Era

Reference 38

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This paper cites Multi-Agent Cooperation and the Emergence of (Natural) Language.

Provably Optimal Learning Algorithms for Assistance Games Multi-Agent Cooperation and the Emergence of (Natural) Language

Reference 39

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Observation 1b46fa3a-c47c-4048-80bd-d3ef919f605f · outbound

This paper cites Learning and approximating the optimal strategy to commit to.

Provably Optimal Learning Algorithms for Assistance Games Learning and approximating the optimal strategy to commit to

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.956196Z

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Observation a98108da-74fd-43f8-954c-90aa50674464 · outbound

This paper cites Ease-of-teaching and language structure from emergent communication.

Provably Optimal Learning Algorithms for Assistance Games Ease-of-teaching and language structure from emergent communication

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.901456Z

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Observation 54c138e6-84ad-412d-afce-637aa1cc1d26 · outbound

This paper cites The geometry of logconcave functions and sampling algorithms.

Provably Optimal Learning Algorithms for Assistance Games The geometry of logconcave functions and sampling algorithms

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.866640Z

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Observation 267b4bde-0474-41db-8f07-ee673a267b12 · outbound

This paper cites Decentralized stochastic control.

Provably Optimal Learning Algorithms for Assistance Games Decentralized stochastic control

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.946719Z

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Observation 12a314d0-525d-4818-971a-7cedcc6b87bf · outbound

This paper cites An efficient, generalized bellman update for cooperative inverse reinforcement learning.

Provably Optimal Learning Algorithms for Assistance Games An efficient, generalized bellman update for cooperative inverse reinforcement learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.896770Z

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This paper cites On team decision problems with nonclassical information structures.

Provably Optimal Learning Algorithms for Assistance Games On team decision problems with nonclassical information structures

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.888262Z

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Observation 3bc154b7-f88d-4e30-ae10-bb4020610fae · outbound

This paper cites Decentralized stochastic control with partial history sharing: A common information approach.

Provably Optimal Learning Algorithms for Assistance Games Decentralized stochastic control with partial history sharing: A common information approach

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.890167Z

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Observation af7ee05b-0f85-42ba-b70d-82dc52d3a22d · outbound

This paper cites Learning optimal strategies to commit to.

Provably Optimal Learning Algorithms for Assistance Games Learning optimal strategies to commit to

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.937170Z

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This paper cites Team decision problems.

Provably Optimal Learning Algorithms for Assistance Games Team decision problems

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.914067Z

Source-reported events for the cited work

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Observation 9be6ac91-83e7-4e64-8acd-97a7266c81ba · outbound

This paper cites Enhance the compositionality of emergent language by iterated learning.

Provably Optimal Learning Algorithms for Assistance Games Enhance the compositionality of emergent language by iterated learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.925855Z

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Observation 2cd6b146-894b-4690-8cff-0593b4eb34fc · outbound

This paper cites "LazImpa": Lazy and Impatient neural agents learn to communicate efficiently.

Provably Optimal Learning Algorithms for Assistance Games "LazImpa": Lazy and Impatient neural agents learn to communicate efficiently

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-07-10T13:47:05.757416Z

Source-reported events for the cited work

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Observation 2777f177-e6a3-4428-858e-bf6239ac515d · outbound

This paper cites Online submodular maximization via online convex optimization.

Provably Optimal Learning Algorithms for Assistance Games Online submodular maximization via online convex optimization

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.924128Z

Source-reported events for the cited work

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Observation b2c7ea86-43b5-4c73-a428-585a25a25268 · outbound

This paper cites Benefits of assistance over reward learning, 2020.

Provably Optimal Learning Algorithms for Assistance Games Benefits of assistance over reward learning, 2020

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.908577Z

Source-reported events for the cited work

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Observation 7c36ff80-d220-462a-8122-cfb2050fe256 · outbound

This paper cites Online learning and online convex optimization.

Provably Optimal Learning Algorithms for Assistance Games Online learning and online convex optimization

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.935149Z

Source-reported events for the cited work

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Observation 6599fcea-469f-4e19-a13c-4ce0fa6fb1e5 · outbound

This paper cites Lazy oco: Online convex optimization on a switching budget.

Provably Optimal Learning Algorithms for Assistance Games Lazy oco: Online convex optimization on a switching budget

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.899435Z

Source-reported events for the cited work

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Observation d0307b8b-1f4e-48a6-b5b9-01fc6804edca · outbound

This paper cites Bayesian modeling of human--ai complementarity.

Provably Optimal Learning Algorithms for Assistance Games Bayesian modeling of human--ai complementarity

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.938812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8cf58629-1e69-4522-b742-a48d4e569a35 · outbound

This paper cites Nash equilibria for an evolutionary language game.

Provably Optimal Learning Algorithms for Assistance Games Nash equilibria for an evolutionary language game

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.976875Z

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Observation fd09f9c0-6241-469a-bd9e-63219cce8e7b · outbound

This paper cites Learning to Complement Humans.

Provably Optimal Learning Algorithms for Assistance Games Learning to Complement Humans

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-07-10T13:47:05.754960Z

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Observation 6768246d-b293-4de1-a3f7-1c3cfd14ff97 · outbound

This paper cites Who leads and who follows in strategic classification? Advances in Neural Information Processing Systems, 34: 0 15257--15269, 2021.

Provably Optimal Learning Algorithms for Assistance Games Who leads and who follows in strategic classification? Advances in Neural Information Processing Systems, 34: 0 15257--15269, 2021

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-10T13:47:05.934595Z

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