Organization of the information flow in the perception-action loop of evolved agents
Organization of the information flow in the perception-action loop of evolved agents
复制标题
进化智能体感知-行动循环中信息流的组织
DOI：
--
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
Chrystopher L. Nehaniv
中科院分区：
文献类型：
--
作者：
A. S. Klyubin;D. Polani;Chrystopher L. Nehaniv
自然界中的传感器进化旨在改进从环境中获取信息的能力，并且与适应性和鲁棒性的选择压力密切相关。该领域近期的研究工作旨在以一种形式化的信息论方式研究感知 - 行动回路。这为从原理上全面理解自然界中传感器进化的机制铺平了道路，并为人工传感器进化机制的设计提供了见解。在我们的论文中，我们研究了智能体的感知 - 行动回路。我们将有限状态自动机进化为智能体控制器，以在一个简单的虚拟世界中解决信息获取任务，并研究信息流是如何通过进化来组织的。我们对进化后的自动机和信息流的分析，为进化如何组织感官信息获取、记忆、处理和行动选择提供了见解。此外，将结果与基于信息瓶颈原理的理想信息提取方案进行了比较。
Sensor evolution in nature aims at improving the acquisition of information from the environment and is intimately related with selection pressure towards adaptivity and robustness. Recent work in the area aims at studying the perception-action loop in a formalized information-theoretic manner. This paves the way towards a principled and general understanding of the mechanisms guiding the evolution of sensors in nature and provides insights into the design of mechanisms of artificial sensor evolution. In our paper we study the perception-action loop of agents. We evolve finite-state automata as agent controllers to solve an information acquisition task in a simple virtual world and study how the information flow is organized by evolution. Our analysis of the evolved automata and the information flow provides insight into how evolution organizes sensoric information acquisition, memory, processing and action selection. In addition, the results are compared to ideal information extraction schemes following from the Information Bottleneck principle.