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algorithms

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Exit-and-Join Dynamics Enable Decentralized Coalition Formation in Multi-Agent Systems Technology
Artificial Intelligence #coalition formation#decentralized

Exit-and-Join Dynamics Enable Decentralized Coalition Formation in Multi-Agent Systems

A new paper by Zhu and Quanyan presents a decentralized dynamical process for coalition formation driven by unilateral exit-and-join decisions. Agents evaluate moves using the Aumann-Dreze value, leading to equilibrium characterizations and stability analysis through Lyapunov representations.

Jul 8, 2026 1 source
Algorithmic Management in India's Gig Economy: The Case for a Hybrid Human-AI Governance Model Technology
Artificial Intelligence #gig economy#ai

Algorithmic Management in India's Gig Economy: The Case for a Hybrid Human-AI Governance Model

A new study by Kumar, Omir, Narayanan, and Krishnan examines the impact of AI and digital technologies on India's blue-collar gig economy. Through interviews with 16 gig workers and 21 stakeholders, the research uncovers opaque algorithmic systems that produce inequitable outcomes and fail to reward additional labor proportionately. The authors propose an 'Algorithmic-Human Manager' framework that combines technological efficiency with human accountability.

Jun 20, 2026 1 source
Zero-Inflated Gaussian EDAs Enable Parameter-Space Sparsity Without Hand-Crafted Operators Technology
Artificial Intelligence #estimation-of-distribution#algorithms

Zero-Inflated Gaussian EDAs Enable Parameter-Space Sparsity Without Hand-Crafted Operators

Researchers propose multivariate zero-inflated Gaussian distributions as sampling laws for estimation-of-distribution algorithms (EDAs), enabling parameter-space sparsity without hand-crafted operators. The ZIG-EDA jointly optimizes sparsity patterns and active values, and on the Lunar Lander benchmark it converges faster and achieves higher returns than dense and sparse alternatives.

Jun 20, 2026 1 source
RACL: Reasoning-Agent Control Layers Show Promise for Continuous Metaheuristic Learning in Vehicle Routing Technology
Artificial Intelligence #racl#reasoning-agent

RACL: Reasoning-Agent Control Layers Show Promise for Continuous Metaheuristic Learning in Vehicle Routing

A new research paper introduces Reasoning-Agent Control Layers (RACL), a method that places an AI reasoning agent above existing metaheuristic optimizers to discover and validate control rules. Tested on vehicle routing, RACL outperformed baseline policies in 21 of 21 cases, achieving average cost reductions of up to 8.3%.

Jun 20, 2026 1 source
CoT Transformers Can Efficiently Simulate Word RAM Algorithms, New Research Shows Technology
Artificial Intelligence #artificial intelligence#transformers

CoT Transformers Can Efficiently Simulate Word RAM Algorithms, New Research Shows

A new paper on arXiv demonstrates that chain-of-thought (CoT) transformers can efficiently simulate Word RAM algorithms, which are more intuitive and efficient than Turing machines for discussing algorithms. The authors show that with poly-logarithmic overhead, CoT transformers can execute algorithms like sorting and Dijkstra's in near-optimal steps, and extend the result to practical settings like continuous CoT and hybrid architectures.

Jun 20, 2026 1 source