论文标题
Escell：紧急象征性蜂窝语言
ESCELL: Emergent Symbolic Cellular Language
论文作者
论文摘要
我们提出了埃斯埃尔（Escell），这是一种开发出关于细胞推理的多种代理之间的紧急象征性语言的方法。我们展示了代理如何以类似于人类语言的符号的形式进行合作和成功交流，以以参考游戏的形式完成任务（刘易斯的信号游戏）。以一种游戏形式，一个发件人和接收器观察了来自5种不同单元格表型的一组单元。发件人被告知一个单元格是一个目标，可以从固定的任意词汇大小向接收器发送一个符号。接收器依赖符号中的信息来识别目标单元。我们培训发件人和接收器网络，以在他们之间开发天生的新兴语言以完成这项任务。我们观察到，网络能够成功地从5种不同表型中识别细胞，精度为93.2％。我们还引入了一种新形式的信号游戏，其中显示了发送者的一个图像，而不是接收器看到的所有图像。网络成功地开发了一种新兴语言，以获得77.8％的识别精度。
We present ESCELL, a method for developing an emergent symbolic language of communication between multiple agents reasoning about cells. We show how agents are able to cooperate and communicate successfully in the form of symbols similar to human language to accomplish a task in the form of a referential game (Lewis' signaling game). In one form of the game, a sender and a receiver observe a set of cells from 5 different cell phenotypes. The sender is told one cell is a target and is allowed to send one symbol to the receiver from a fixed arbitrary vocabulary size. The receiver relies on the information in the symbol to identify the target cell. We train the sender and receiver networks to develop an innate emergent language between themselves to accomplish this task. We observe that the networks are able to successfully identify cells from 5 different phenotypes with an accuracy of 93.2%. We also introduce a new form of the signaling game where the sender is shown one image instead of all the images that the receiver sees. The networks successfully develop an emergent language to get an identification accuracy of 77.8%.
