LEARNING HIGH-LEVEL BEHAVIORS FROM DEMONSTRATION THROUGH SEMANTIC NETWORKS

被引：8

作者：

Fonooni, Benjamin ^{[1
]}

Hellstrom, Thomas ^{[1
]}

Janlert, Lars-Erik ^{[1
]}

机构：

[1] Umea Univ, Dept Comp Sci, SE-90187 Umea, Sweden

来源：

ICAART: PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1 | 2012年

关键词：

Learning from Demonstration; High-Level Behaviors; Semantic Networks; Robot Learning;

D O I：

10.5220/0003834304190426

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we present an approach for high-level behavior recognition and selection integrated with a low-level controller to help the robot to learn new skills from demonstrations. By means of Semantic Network as the core of the method, the robot gains the ability to model the world with concepts and relate them to low-level sensory-motor states. We also show how the generalization ability of Semantic Networks can be used to extend learned skills to new situations.

引用

页码：419 / 426

页数：8

共 24 条

[1]

[Anonymous], THESIS U SO CALIFORN

[2]

[Anonymous], IEEE SMC INT C DISTR

[3] Task planning under uncertainty using a spreading activation network [J].

Bagchi, S ;

Biswas, G ;

Kawamura, K .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2000, 30 (06) :639-650

[4]

Billard A., 2008, Robot Programming by Demonstration

[5]

Billing E. A., 2010, P IEEE INT C ROB AUT

[6]

Billing EA, 2010, PALADYN, V1, P1, DOI DOI 10.2478/S13230-010-0001-5

[7]

Brown A., 2000, How People Learn: Brain, Mind, Experience, and School

[8]

Byrne R.W., 1994, P223

[9]

Byrne R. W., 1998, J BEHAV BRAIN SCI, V16

[10] An introduction to the anchoring problem [J].

Coradeschi, S ;

Saffiotti, A .

ROBOTICS AND AUTONOMOUS SYSTEMS, 2003, 43 (2-3) :85-96

← 1 2 3 →