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Extracting Episodic Memory Feature Relevance Without Domain Knowledge

机译:在没有领域知识的情况下提取情景记忆特征相关性

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Episodic memory provides many important capabilities to a cognitive architecture. One of the challenges of creating a general episodic memory system is to be effective when given no information about the agent's task.In this paper, we present an effective algorithm for detecting the relevance of the features of episodic memories while only being told when an agent completes a goal. We demonstrate this algorithm using an episodic learning agent in a task that provides the agent with a mix of relevant and irrelevant features. The episodic learner outperforms a variant Q-Learning algorithm that has proven effective in the past.
机译:情景记忆为认知体系结构提供了许多重要的功能。创建通用情节记忆系统的挑战之一是在不提供有关代理任务的信息的情况下如何有效。在本文中,我们提出了一种有效的算法,用于检测情节记忆特征的相关性,而仅当代理被告知时完成一个目标。我们在任务中使用情景学习代理演示了该算法,该任务为代理提供了相关特征和不相关特征的混合。情节学习器的性能优于过去证明有效的变体Q学习算法。

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