论文标题
在速度和预算限制下探索任务的合作解决方案
Cooperative Solutions to Exploration Tasks Under Speed and Budget Constraints
论文作者
论文摘要
我们提出了一个多代理系统，代理可以合作解决依赖任务系统，代理具有探索解决方案空间，推断以及在预算有限的信息下查询信息的能力。当较旧的解决方案到期时，代理会进行解决方案空间的重新探索，因此能够适应环境中的动态变化。 We investigate the effects of task dependencies, with highly-dependent graph $G_{40}$ (a well-known program graph that contains $40$ highly interlinked nodes, each representing a task) and less-dependent graphs $G_{18}$ (a program graph that contains $18$ tasks with fewer links), increasing the speed of the agents and the complexity of the problem space and the query budgets available to agents.具体而言，我们评估了代理商速度和查询预算之间的权衡。在实验过程中，我们观察到，单个代理的速度只会将系统性能提高到一定点，并且增加速度更快的代理的数量可能无法改善由于任务依赖性而导致的系统性能。根据“马修效应”，预算分配期间更快的代理会增强系统性能。我们还观察到，将更多的预算分配给更快的代理可以为较不依赖的系统提供更好的性能，但是增加代理的数量为高度依赖的系统提供了更好的性能。
We present a multi-agent system where agents can cooperate to solve a system of dependent tasks, with agents having the capability to explore a solution space, make inferences, as well as query for information under a limited budget. Re-exploration of the solution space takes place by an agent when an older solution expires and is thus able to adapt to dynamic changes in the environment. We investigate the effects of task dependencies, with highly-dependent graph $G_{40}$ (a well-known program graph that contains $40$ highly interlinked nodes, each representing a task) and less-dependent graphs $G_{18}$ (a program graph that contains $18$ tasks with fewer links), increasing the speed of the agents and the complexity of the problem space and the query budgets available to agents. Specifically, we evaluate trade-offs between the agent's speed and query budget. During the experiments, we observed that increasing the speed of a single agent improves the system performance to a certain point only, and increasing the number of faster agents may not improve the system performance due to task dependencies. Favoring faster agents during budget allocation enhances the system performance, in line with the "Matthew effect." We also observe that allocating more budget to a faster agent gives better performance for a less-dependent system, but increasing the number of faster agents gives a better performance for a highly-dependent system.
