Stein Gary, Gonzalez Avelino J
School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32826, USA.
IEEE Trans Syst Man Cybern B Cybern. 2011 Jun;41(3):792-804. doi: 10.1109/TSMCB.2010.2091955. Epub 2010 Dec 17.
This paper describes a two-phase approach for automating the agent-building process when the agent is to perform tactical tasks. The research is inspired by how humans learn-first by observation of a teacher's performance and then by practicing the performance themselves. The objectives of this approach are to produce a high-performing agent that 1) approaches or exceeds the proficiency of a human and 2) does so in a human-like manner. We accomplish these objectives by combining observational learning with experiential learning. These processes are executed sequentially, with the former creating a competent but somewhat limited human-like model from scratch, and the latter improving its performance without significantly eroding its human-like qualities. The process is described in detail, and test results confirming our hypothesis are described.
本文描述了一种两阶段方法，用于在智能体执行战术任务时自动执行智能体构建过程。该研究的灵感来源于人类的学习方式——首先观察教师的表现，然后自己练习该表现。这种方法的目标是生成一个高性能智能体，该智能体要做到：1）接近或超过人类的熟练程度；2）以类似人类的方式做到这一点。我们通过将观察学习与经验学习相结合来实现这些目标。这些过程按顺序执行，前者从零开始创建一个有能力但在某种程度上有限的类人模型，后者在不显著削弱其类人特质的情况下提高其性能。文中详细描述了该过程，并描述了证实我们假设的测试结果。
