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Apr, 2025
通过奖励塑造和课程学习实现最佳组织修复
Achieving Optimal Tissue Repair Through MARL with Reward Shaping and Curriculum Learning
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Muhammad Al-Zafar Khan, Jamal Al-Karaki
TL;DR
本研究解决了优化组织修复过程中的空白，提出了一种多智能体强化学习（MARL）框架，结合了分子信号建模、类神经电化学通信和生物启发的奖励函数。实验结果表明，所提方法能够产生新兴的修复策略，如动态分泌控制和空间协调，具有显著的潜在影响。
Abstract
In this paper, we present a
Multi-agent reinforcement learning
(MARL) framework for optimizing
Tissue repair
processes using engineered
Biologica
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