Perfecting a Video Game with Game Metrics
Vol 17, No 3: June 2019

Exploration of genetic network programming with two-stage reinforcement learning for mobile robot

Siti Sendari (Universitas Negeri Malang)
Arif Nur Afandi (Universitas Negeri Malang)
Ilham Ari Elbaith Zaeni (Universitas Negeri Malang)
Yogi Dwi Mahandi (Universitas Negeri Malang)
Kotaro Hirasawa (Waseda University)
Hsien-I Lin (National Taipei Univeristy)

Article Info

Publish Date
01 Jun 2019

Abstract

This paper observes the exploration of Genetic Network Programming Two-Stage Reinforcement Learning for mobile robot navigation. The proposed method aims to observe its exploration when inexperienced environments used in the implementation. In order to deal with this situation, individuals are trained firstly in the training phase, that is, they learn the environment with ϵ-greedy policy and learning rate α parameters. Here, two cases are studied, i.e., case A for low exploration and case B for high exploration. In the implementation, the individuals implemented to get experience and learn a new environment on-line. Then, the performance of learning processes are observed due to the environmental changes.

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Journal Info
Perfecting a Video Game with Game Metrics
Website

Abbrev

TELKOMNIKA

Publisher

Universitas Ahmad Dahlan

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...