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(2019b); however, in general settings it is not known how to best play against mean-based learners, even if the agent knows everything about the learners, and can predict with certainty what actions they would take as a function of the history of play
from the top result below
https://arxiv.org/html/2407.04889v1
(2019b); however, in general settings it is not known how to best play against mean-based learners, even if the agent knows everything about the learners, and can predict with certainty what actions they would take as a function of the history of play
https://arxiv.org/html/2407.18010v2
Since acting at each available opportunity would accumulate prohibitively large costs, the resulting decision problem is one in which players must make strategic decisions about when to execute actions in addition to their choice of action
https://arxiv.org/html/2608.03452v1
Probing five architectures, twelve trained models each, under lemma-disjoint cross-validation with controls and surface baselines, we show that the models encode the L-shaped class itself, not just its visible alternations
https://arxiv.org/html/2607.28847v1
2 Proof of Lemma 1 (Optimality of Boundary Crossing)
D
https://arxiv.org/list/cs.CL/new
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https://arxiv.org/list/cs.AI/new
A core calculus gives an effect-confinement lemma and six safety properties
https://arxiv.org/html/2608.02943v1
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arXiv:2608
https://arxiv.org/html/2607.24970v2
Said differently, if each application targets one of nn schools randomly, how many applications do I need for each school to receive at least one application
https://arxiv.org/html/2205.01882v5
2 Details of the DVD Dataset
M Additional Empirical Application: Fishing-site Choice
M
https://arxiv.org/html/2407.00419v1
Two natural assumptions in such settings are that: 1) all agents in the population are individually rational learners, and 2) when any two members of the population are paired together, with high-probability they will achieve at least the same utility as they would under some Pareto efficient equilibrium strategy
https://arxiv.org/html/2407.00575v3
Even worse, the manager would need to collect the parameters periodically if they are time-varying, and then solve the large-scale optimization problem again
https://arxiv.org/html/2607.22511v2
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https://arxiv.org/html/2508.08980v3
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arXiv:2508
https://arxiv.org/html/2604.05327v4
This version:
I would like to thank Xu Cheng, Frank Diebold, Wayne Gao, George Mailath, and seminar participants at Chicago Booth, Paris Econometrics Seminar, Toulouse School of Economics, and the University of Pennsylvania for valuable discussions and comments that substantially improved this article
https://arxiv.org/html/2608.03703v1
begun on July 20, 2026; the present version is dated August 4, 2026. Claude Opus 5 and Fable 5 provided research assistance throughout, spanning code development, data construction and empirical analysis, and the drafting of the manuscript.
https://arxiv.org/html/2608.02609v1
A student can type “The king rules the land” and receive a clay tablet bearing the cuneiform equivalent; a museum visitor can render their name in the world’s oldest script; a researcher can back-translate English glosses into Akkadian for data augmentation
https://arxiv.org/html/2608.02800v1
It chooses the fee paid by third-party sellers, the visibility its first-party products receive in search and recommendation, and the price of those products
https://arxiv.org/pdf/2006.02318
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https://arxiv.org/html/2403.16413v3
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https://arxiv.org/list/cs.DS/new
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[1] arXiv:2608
https://arxiv.org/html/2608.02909v1
In practice, most researchers use the generated variables “as is” on the right-hand side of the regression, as if they captured the true, latent variable of interest
https://arxiv.org/list/cs.CR/new
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New submissions (showing 32 of 32 entries)
[1] arXiv:2608
https://arxiv.org/html/2608.03504v1
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arXiv:2608
https://arxiv.org/html/2407.08254v2
We prove that our approach guarantees that the average joint action of all agents converges to a Nash equilibrium (NE) if every agent applies the same RM procedure in any cooperative game with a submodular utility function
https://arxiv.org/html/2407.06328v2
In such dynamic game settings, if agents have limited capabilities for observing the game’s state, they must estimate it and use this estimate to infer expected payoffs and select one of available strategies
https://arxiv.org/html/2608.03573v1
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arXiv:2608
https://arxiv.org/html/2407.20187v1
If there are more blue nodes than red nodes then we say blue is the majority
https://arxiv.org/html/2309.08431v3
Concentration risk refers to the decrease in fee revenue if the marginal exchange rate (akin to the midprice in a limit order book) in the pool exits the LP’s range of liquidity
https://arxiv.org/html/2511.06451v1
1 Data Protocol (arXiv Release)
Synthetic risk–neutral generator
https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries