Flexible multi-agent decision making under time pressure
Flexible multi-agent decision making under time pressure
复制标题
时间压力下灵活的多智能体决策
DOI：
10.1109/tsmca.2005.851797
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
P. Gmytrasiewicz
中科院分区：
文献类型：
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作者：
Sanguk Noh;P. Gmytrasiewicz
自治代理需要大量的计算资源来执行合理的决策。当环境中存在其他试剂时，这些要求甚至更加严格。在这些设置中，代理的替代行为的质量不仅取决于环境的状态，而且还取决于其他代理的行为，这反过来又取决于其他代理对世界的信念，他们的偏好，并进一步取决于其他代理对他人的信念，当有大量的代理人在场时，当必须在时间压力下做出决定时，复杂性变得令人望而却步。在本文中，我们调查的策略，旨在驯服的计算负担，使用离线计算与在线推理。我们研究两种方法。首先，我们使用离线编译的规则来约束在线推理过程中考虑的替代行为。这种方法使开销最小化，但对当前情况的实时需求变化不敏感。其次，我们使用离线计算的性能配置文件和紧急性的概念（即，时间值）在线计算以选择在线审议期间要包括的信息量。这种方法可以适应各种级别的实时需求，但会产生一些与迭代深化相关的开销。我们测试我们的框架在一个模拟的防空领域的实验。实验表明，这两个程序是有效的，在减少计算时间，同时提供良好的性能下的时间压力。
Autonomous agents need considerable computational resources to perform rational decision making. These demands are even more severe when other agents are present in the environment. In these settings, the quality of an agent's alternative behaviors depends not only on the state of the environment, but also on the actions of other agents, which in turn depend on the others' beliefs about the world, their preferences, and further on the other agents' beliefs about others, and so on. The complexity becomes prohibitive when large number of agents are present and when decisions have to be made under time pressure. In this paper, we investigate strategies intended to tame the computational burden by using offline computation in conjunction with online reasoning. We investigate two approaches. First, we use rules compiled offline to constrain alternative actions considered during online reasoning. This method minimizes overhead, but is not sensitive to changes in real-time demands of the situation at hand. Second, we use performance profiles computed offline and the notion of urgency (i.e., the value of time) computed online to choose the amount of information to be included during online deliberation. This method can adjust to various levels of real-time demands, but incurs some overhead associated with iterative deepening. We test our framework with experiments in a simulated anti-air defense domain. The experiments show that both procedures are effective in reducing computation time while offering good performance under time pressure.