robotics experts discussed the implications of milps for future automation.
机器人专家讨论了多智能体学习问题对未来自动化的影响。
the research paper introduces a new algorithm for solving milps efficiently.
这篇研究论文介绍了一种有效解决多智能体学习问题的新算法。
engineers optimize network routing by formulating complex milps.
工程师通过构建复杂的多智能体学习问题来优化网络路由。
understanding milps is crucial for advanced multi-robot coordination.
理解多智能体学习问题对于先进的多机器人协调至关重要。
the software toolkit simplifies the definition and solution of milps.
该软件工具包简化了多智能体学习问题的定义和求解。
scalability remains a significant challenge when processing large-scale milps.
在处理大规模多智能体学习问题时，可扩展性仍然是一个重大挑战。
modern solvers can handle stochastic milps with remarkable speed.
现代求解器能够以惊人的速度处理随机多智能体学习问题。
the workshop focused on practical applications of milps in logistics.
研讨会重点讨论了多智能体学习问题在物流领域的实际应用。
decentralized control strategies often rely on decomposing milps.
分散控制策略通常依赖于分解多智能体学习问题。
academic journals frequently publish studies regarding the convergence of milps.
学术期刊经常发表有关多智能体学习问题收敛性的研究。
he dedicated his phd thesis to the theoretical bounds of milps.
他将他的博士论文致力于多智能体学习问题的理论界限研究。
collaborative decision-making systems utilize milps to balance competing objectives.
协作决策系统利用多智能体学习问题来平衡相互竞争的目标。
robotics experts discussed the implications of milps for future automation.
机器人专家讨论了多智能体学习问题对未来自动化的影响。
the research paper introduces a new algorithm for solving milps efficiently.
这篇研究论文介绍了一种有效解决多智能体学习问题的新算法。
engineers optimize network routing by formulating complex milps.
工程师通过构建复杂的多智能体学习问题来优化网络路由。
understanding milps is crucial for advanced multi-robot coordination.
理解多智能体学习问题对于先进的多机器人协调至关重要。
the software toolkit simplifies the definition and solution of milps.
该软件工具包简化了多智能体学习问题的定义和求解。
scalability remains a significant challenge when processing large-scale milps.
在处理大规模多智能体学习问题时，可扩展性仍然是一个重大挑战。
modern solvers can handle stochastic milps with remarkable speed.
现代求解器能够以惊人的速度处理随机多智能体学习问题。
the workshop focused on practical applications of milps in logistics.
研讨会重点讨论了多智能体学习问题在物流领域的实际应用。
decentralized control strategies often rely on decomposing milps.
分散控制策略通常依赖于分解多智能体学习问题。
academic journals frequently publish studies regarding the convergence of milps.
学术期刊经常发表有关多智能体学习问题收敛性的研究。
he dedicated his phd thesis to the theoretical bounds of milps.
他将他的博士论文致力于多智能体学习问题的理论界限研究。
collaborative decision-making systems utilize milps to balance competing objectives.
协作决策系统利用多智能体学习问题来平衡相互竞争的目标。
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