Adaptability and diversity in simulated turn-taking behavior
Adaptability and diversity in simulated turn-taking behavior
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DOI：
10.1162/1064546041766442
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发表时间：
2004-09-01
期刊：
影响因子：
2.6
通讯作者：
Ikegami, T
中科院分区：
文献类型：
--
作者：
Iizuka, H;Ikegami, T
在耦合智能体系统中模拟话轮转换行为。每个代理被建模为一个移动的机器人与两个轮子。一个递归神经网络用于产生电机输出和保持内部动态。代理开发轮流在一个二维的竞技场，使网络结构的演变。轮流使用代理的规则或混乱行为来建立。结果发现，混沌轮的反应更敏感的输入从其他代理。相反，常规转弯者由于其受限的动力学特性而对噪声输入具有相对鲁棒性。从许多观察，包括轮流与虚拟代理，我们声称，有一个鲁棒性和适应性之间的互补关系。此外，通过研究来自不同GA代的代理的重新耦合，我们报告了一种新的话轮转换行为的出现。混沌话轮转换者的另一个特点是有可能合成一种新的互动形式。
Turn-taking behavior is simulated in a coupled-agents system. Each agent is modeled as a mobile robot with two wheels. A recurrent neural network is used to produce the motor outputs and to hold the internal dynamics. Agents are developed to take turns on a two-dimensional arena by causing the network structures to evolve. Turn taking is established using either regular or chaotic behavior of the agents. It is found that chaotic turn takers are more sensitive in response to inputs from the other agent. Conversely, regular turn takers are comparatively robust against noisy inputs, owing to their restricted dynamics. From many observations, including turn taking with virtual agents, we claim that there is a complementary relationship between robustness and adaptability. Furthermore, by investigating the recoupling of agents from different GA generations, we report the emergence of a new turn-taking behavior. Potential for synthesizing a new form of interaction is another characteristic of chaotic turn takers.