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An integrated epigenetic robot architecture via context-influenced long-term memory

机译:通过上下文影响的长期记忆的集成表观机器人体系结构

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In this paper, we present a conceptual design for a context-influenced Long-Term Memory architecture. The notion of context is used as a means to organize the information flow between the Working Memory and Long-Term Memory components. In particular, we discuss the major influence of the notion of context within the Episodic Memory on the Semantic and Procedural Memory, respectively. In other words, we address how the occurrence of specific events in time impacts on the meaning of those events and the subsequent use of objects through robot actions. The general architecture design and its implementation in a simulated scenario are described. Such issues as memory items representation, individual structures of Long-Term Memory components, as well as memory-based recognition and item retrieval processes, are discussed in detail.
机译:在本文中,我们提出了一个受上下文影响的长期内存体系结构的概念设计。上下文的概念用作组织工作内存和长期内存组件之间的信息流的一种方式。特别是,我们分别讨论了情境记忆中情境概念对语义和过程记忆的主要影响。换句话说,我们通过机器人动作解决特定事件的及时发生如何影响这些事件的含义以及对象的后续使用。描述了通用架构设计及其在模拟场景中的实现。详细讨论了诸如存储项表示,长期存储组件的各个结构以及基于存储的识别和项检索过程之类的问题。

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