• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Agents and data mining interaction >Real-Time Sensory Pattern Mining for Autonomous Agents
【24h】

Real-Time Sensory Pattern Mining for Autonomous Agents

机译：自治代理的实时感知模式挖掘

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Autonomous agents are systems situated in dynamic environments. They pursue goals and satisfy their needs by responding to external events from the environment. In these unpredictable conditions, the agents' adaptive skills are a key factor for their success. Based on previous interactions with its environment, an agent must learn new knowledge about it, and use that information to guide its behavior throughout time. In order to build more believable agents, we need to provide them with structures that represent that knowledge, and mechanisms that update them overtime to reflect the agents' experience. Pattern mining, a subfield of data mining, is a knowledge discovery technique which aims to extract previously unknown associations and causal structures from existing data sources. In this paper we propose the use of pattern mining techniques in autonomous agents to allow the extraction of sensory patterns from the agent's perceptions in realtime. We extend some structures used in pattern mining and employ a statistical test to allow an agent of discovering useful information about the environment while exploring it.
机译：自治代理是位于动态环境中的系统。他们通过应对环境中的外部事件来追求目标并满足他们的需求。在这些不可预测的条件下，特工的适应能力是他们成功的关键因素。基于先前与环境的交互，代理必须学习有关它的新知识，并使用该信息来指导其在整个时间内的行为。为了建立更可信的代理，我们需要为他们提供代表该知识的结构，并通过超时更新其机制以反映代理的经验的机制。模式挖掘是数据挖掘的子领域，是一种知识发现技术，旨在从现有数据源中提取以前未知的关联和因果结构。在本文中，我们建议在自主主体中使用模式挖掘技术，以允许从主体的感知中实时提取感官模式。我们扩展了模式挖掘中使用的某些结构，并采用了统计测试，以允许代理在探索环境时发现有关环境的有用信息。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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