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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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4 results for “MMO”

Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networkscs.LG

Neural MMO simulates MMOs to study multiagent intelligence.

problem Limited research environments for multiagent intelligence.

method Developed a new game environment inspired by MMOs.

result Standard methods can learn interesting behaviors in MMOs.

multiagent systems reinforcement learning game environments emergent behaviors policy gradient

2020-01-31abs ↗pdf ↗

Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agentscs.MA

A game environment simulates competition among many agents for resources.

problem Understanding large-scale multiagent interactions and resource competition.

method Developed a persistent, massively multiplayer AI environment.

result Population size affects the development of skillful behaviors and niche differentiation.

AI Multiagent Systems Resource Competition Persistent Environment MMO

2019-03-02abs ↗pdf ↗

Marketing Mix Optimization with Practical Constraintsmath.OC

Optimizes marketing strategies with practical constraints.

problem Adjusting marketing activities with minimum and maximum changes.

method Formulated as a mixed integer nonlinear program (MINLP), reformulated for computational efficiency.

result Significant improvements in solution process for realistic problems.

marketing mix optimization practical constraints MINLP reformulation integer programming

2021-01-11abs ↗pdf ↗

Principled Algorithms for Optimizing Generalized Metrics in Multi-Label Learningcs.LG

Develops algorithms for optimizing multi-label metrics with provable guarantees.

problem Optimizing complex multi-label metrics like F-measure and Jaccard index.

method Principled learning algorithms based on H-consistency for generalized metrics.

result Provable

H

-consistency bounds for multi-label metric optimization.

multi-label learning generalized metrics H-consistency surrogate loss EUM framework

2026-05-27abs ↗pdf ↗