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Songxin Lei

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A Game-Theoretic Spatio-Temporal Reinforcement Learning Framework for Collaborative Public Resource Allocation

This work formulations CPRA as a potential game and construct the potential function based on the objective function of CPRA, laying a theoretical foundation for approximating the Nash equilibrium of this NP-hard problem, and proposes a Game-Theoretic Spatio-Temporal Reinforcement Learning (GSTRL) framework to solve it...

Songxin Lei, Qiong-Yan Wang, Yanchen Zhu et al. · 2 citations

Reinforcement Learning for Delivery Drone-Based Participatory Sensing in Dynamic Environments

A Two TimeScale Reinforcement Learning framework (TSRL), which separates decision-making into two cooperative layers and significantly outperforms baselines, achieving average system profit improvements of 20.1% in Hangzhou and 46.6% in Shanghai.

Xin Ouyang, Songxin Lei, Xusen Guo et al. · 0 citations
Preprint Aug 2026

MemoryCPT: An End-to-End Agent Memory Framework for Cost-Performance Trade-off

Experiments on LoCoMo and LongMemEval show that MemoryCPT improves the cost-performance trade-off over the evaluated baselines, while ablation and sensitivity analyses characterize the contributions of its components and the effects of key design choices.

Songxin Lei, Kun Ouyang, Wei-Lin Ruan et al. · 1 citation · ⚡1

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