...
首页> 外文期刊>Cognitive Systems Research >The pattern theory of self in artificial general intelligence: A theoretical framework for modeling self in biologically inspired cognitive architectures
【24h】

The pattern theory of self in artificial general intelligence: A theoretical framework for modeling self in biologically inspired cognitive architectures

机译:人工综合情报的自我模式理论:一种在生物学启发认知架构中建模自我的理论框架

获取原文
获取原文并翻译 | 示例
           

摘要

In an attempt to provide a unified account for a vast literature discussing a multiplicity of selves, Gallagher (2013) has proposed a pattern theory of self. Subsequent discussion on this account has led to a concern that the pattern theory, as originally presented, stands as a mere list of aspects that fails to explain how they are related in real-time. We suggest that one way to address these criticisms, and further develop the pattern theory of self is by exploring how it can be used to aid research on self in artificial general intelligence, especially in the context of biologically inspired cognitive architectures. We furthermore propose a conceptual implementation for actualizing such research in regards to the LIDA (Learning Intelligent Decision Agent) cognitive model. (C) 2019 Elsevier B.V. All rights reserved.
机译:为了提供统一的账户,为讨论多种自我的巨大文学,加拉尔(2013)提出了一种自我的模式理论。随后就本账户的讨论导致了一个令人担忧的是,如最初呈现的那样的模式理论是仅仅是未能解释它们在实时相关的方面的独一无止的方面列表。我们建议解决这些批评的一种方法,进一步发展自我的模式理论是通过探索如何用来援助人工智力的自我研究,特别是在生物学启发认知架构的背景下。我们还提出了一种概念实施,以实现莱达(学习智能决策代理)认知模型的关于赖达的这种研究。 (c)2019 Elsevier B.v.保留所有权利。

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