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

来源：

INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS | 2016年 / 8卷 / 01期

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

页码：5 / 19

页数：15

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