通过个体间选择压力从遗传进化中引导模因
Bootstrapping of memetic from genetic evolution via inter-agent selection pressures
摘要：
我们创建了一个人工系统的代理（注意力为基础的神经网络），有选择地交换信息，以研究出现的模因进化和模因进化的压力如何相互作用与遗传进化的网络权重。我们观察到，代理人施加选择压力的能力是必不可少的模因进化引导自己进入一个状态，既有高保真复制模因，以及随着时间的推移不断产生新的模因。然而，在这个系统中，这种模因“生态”和驱动个体适应性的潜在任务之间的交互很少-涌现的模因层似乎对代理学习解决任务的能力既没有帮助也没有伤害。这些实验的源代码可在https://github.com/GoodAI/memes上获得
英文摘要：
We create an artificial system of agents (attention-based neural networks) which selectively exchange messages with each-other in order to study the emergence of memetic evolution and how memetic evolutionary pressures interact with genetic evolution of the network weights. We observe that the ability of agents to exert selection pressures on each-other is essential for memetic evolution to bootstrap itself into a state which has both high-fidelity replication of memes, as well as continuing production of new memes over time. However, in this system there is very little interaction between this memetic 'ecology' and underlying tasks driving individual fitness - the emergent meme layer appears to be neither helpful nor harmful to agents' ability to learn to solve tasks. Sourcecode for these experiments is available at https://github.com/GoodAI/memes
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
