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Formally, if NnN_{n} measures the maximum neighbourhood size, δn\delta_{n} is the smallest probability of observing a relevant exposure, and nen_{e} is the expected number of sampled units, the paper requires Nn3/2​log⁡(Nn)δn=O​(ne1/2−ξ)\frac{N_{n}^{3/2}\log(N_{n})}{\delta_{n}}=O(n_{e}^{1/2-\xi}) (99) for
from the top result below

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
This version is a work in progress; please feel free to contact me if you find a mistake, think I missed an important contribution, or just want to send a comment

Maximizing utility in multi-agent environments by anticipating the

https://arxiv.org/html/2407.04889v1
Therefore, if an agent is good at anticipating the behavior of the other agents, in particular how they will make decisions in each round as a function of their experience that far, it could try to judiciously make its own decisions over the rounds of the interaction so as to influence the other agents to behave in a

Computation and Language

https://arxiv.org/list/cs.CL/new
Skip to main content System maintenance August 4th and 5th Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computation and Language New submissions Cross-lists Replacements See recent

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
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When LLMs Play the Telephone Game: Cultural Attractors as Conceptual

https://arxiv.org/html/2407.04503v4
In a series of telephone game experiments, we apply a transmission chain design borrowed from the human cultural evolution literature: LLM agents iteratively receive, produce, and transmit texts from the previous to the next agent in the chain

Stochastic Games with Minimally Bounded Action Costs

https://arxiv.org/html/2407.18010v2
1 Introduction 2 Formulation 3 Existence of a Value and Saddle Point Equilibrium 4 Learning in Unknown Environments 4.1 Convergence using Linear Function Approximators 5 Intervention Budget Constraints 6 Discussion on Subcases 7 Related

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https://arxiv.org/pdf/2006.02318
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https://arxiv.org/src/2303.12712
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https://arxiv.org/pdf/2608.01934
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https://arxiv.org/pdf/2609.18842
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https://arxiv.org/pdf/2607.26327v3
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2508.11152
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https://arxiv.org/src/2608.04007
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https://arxiv.org/pdf/2006.00064
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https://arxiv.org/pdf/2608.03494
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https://arxiv.org/pdf/2608.02609
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https://arxiv.org/pdf/2608.02872
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https://arxiv.org/pdf/2608.03411
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https://arxiv.org/src/2608.04009
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https://arxiv.org/src/1910.03771
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https://arxiv.org/pdf/2309.08431
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https://arxiv.org/pdf/2205.11916v2
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https://arxiv.org/src/2608.04003
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https://arxiv.org/src/2104.08691
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https://arxiv.org/src/2402.03300
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https://arxiv.org/src/2212.07841
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https://arxiv.org/pdf/2507.17609
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https://arxiv.org/pdf/2608.01861
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