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Integration of memory systems supporting non-symbolic representations in an architecture for lifelong development of artificial agents
Artificial Intelligence ( IF 5.1 ) Pub Date : 2024-09-12 , DOI: 10.1016/j.artint.2024.104228
François Suro, Fabien Michel, Tiberiu Stratulat

Compared to autonomous agent learning, lifelong agent learning tackles the additional challenge of accumulating skills in a way favourable to long term development. What an agent learns at a given moment can be an element for the future creation of behaviours of greater complexity, whose purpose cannot be anticipated.

中文翻译:


将支持非符号表示的内存系统集成到一个架构中,以实现人工代理的终身开发



与自主代理学习相比,终身代理学习以有利于长期发展的方式解决了积累技能的额外挑战。代理在特定时刻学到的东西可以成为未来创造更复杂行为的要素,其目的无法预测。
更新日期:2024-09-12
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