Priming as a Means to Reduce Ambiguity in Learning from Demonstration

被引:3
|
作者
Fonooni, Benjamin [1 ]
Hellstrom, Thomas [1 ]
Janlert, Lars-Erik [1 ]
机构
[1] Umea Univ, Dept Comp Sci, S-90187 Umea, Sweden
关键词
Learning from Demonstration; Priming; Ant System; Semantic Networks; Ambiguity; Behavior Learning; DISTRIBUTED BEES ALGORITHM; ANT COLONY OPTIMIZATION; REPETITION; IMITATION; ROBOTS; SUPPRESSION; ALLOCATION; BEHAVIOR; MEMORY;
D O I
10.1007/s12369-015-0292-0
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Learning from Demonstration is an established robot learning technique by which a robot acquires a skill by observing a human or robot teacher demonstrating the skill. In this paper we address the ambiguity involved in inferring the intention with one or several demonstrations. We suggest a method based on priming, and a memory model with similarities to human learning. Conducted experiments show that the developed method leads to faster and improved understanding of the intention with a demonstration by reducing ambiguity.
引用
收藏
页码:5 / 19
页数:15
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