首页> 外国专利> REINFORCEMENT LEARNING SYSTEMS COMPRISING A RELATIONAL NETWORK FOR GENERATING DATA ENCODING RELATIONSHIPS BETWEEN ENTITIES IN AN ENVIRONMENT

REINFORCEMENT LEARNING SYSTEMS COMPRISING A RELATIONAL NETWORK FOR GENERATING DATA ENCODING RELATIONSHIPS BETWEEN ENTITIES IN AN ENVIRONMENT

机译:加强学习系统,包括用于生成环境中实体之间的数据的数据编码关系的关系网络

摘要

A neural network system is proposed, including an input network for extracting, from state data, respective entity data for each a plurality of entities which are present, or at least potentially present, in the environment. The entity data describes the entity. The neural network contains a relational network for parsing this data, which includes one or more attention blocks which may be stacked to perform successive actions on the entity data. The attention blocks each include a respective transform network for each of the entities. The transform network for each entity is able to transform data which the transform network receives for the entity into modified entity data for the entity, based on data for a plurality of the other entities. An output network is arranged to receive data output by the relational network, and use the received data to select a respective action.
机译:提出了一种神经网络系统,包括用于从状态数据,从状态数据提取的输入网络,用于在环境中存在或至少潜在存在的多个实体的各个实体数据。实体数据描述了该实体。神经网络包含用于解析该数据的关系网络,其包括一个或多个可以堆叠以对实体数据执行连续动作的关注块。关注块各自包括每个实体的相应变换网络。对于每个实体的变换网络能够基于用于多个其他实体的数据来将变换网络接收到实体的修改实体数据的数据。输出网络被布置为接收由关系网络输出的数据,并使用接收的数据来选择相应的动作。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号