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All Journal Jurnal Ilmu Komputer dan Informasi TRANSIENT: Jurnal Ilmiah Teknik Elektro Jurnal Sistem Komputer Jurnal Kelautan Tropis Edu Komputika Journal JOIV : International Journal on Informatics Visualization Jurnal Teknologi Informasi dan Multimedia Jurnal Ilmu Teknik dan Komputer
Risma Septiana
Departemen Teknik Komputer Universitas Diponegoro
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science

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A Dynamic-Bayesian-Network-Based Approach to Predict Immediate Future Action of an Intelligent Agent Kridalukmana, Rinta; Eridani, Dania; Septiana, Risma
Jurnal Ilmu Komputer dan Informasi Vol. 17 No. 1 (2024): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v17i1.1199

Abstract

Predicting immediate future actions taken by an intelligent agent is considered an essential problem inhuman-autonomy teaming (HAT) in many fields, such as industries and transportation, particularly toimprove human comprehension of the agent as their non-human counterpart. Moreover, the results of suchpredictions can shorten the human response time to gain control back from their non-human counterpartwhen it is required. An example case of HAT that can be benefitted from the action predictor is partiallyautomated driving with the autopilot agent as the intelligent agent. Hence, this research aims to develop anapproach to predict the immediate future actions of an intelligent agent with partially automated drivingas the experimental case. The proposed approach relies on a machine learning method called naive Bayesto develop an action classifier, and the Dynamic Bayesian Network (DBN) as the action predictor. Theautonomous driving simulation software called Carla is used for the simulation. The results show that theproposed approach is applicable to predict an intelligent agent’s three-second time-window immediate futureaction.
Co-Authors Agung Budi Prasetijo Ahmad Fashiha Hastawan Ajub Ajulian Z Aryani, Ritme Cahya Auliya, Novita Chatarina Umbul Wahyuni Dania Eridani Erwin Adriono Gumiwang, Dimas Putu Ike Pertiwi Windasari Marsha, Veliana Maula, Nurinda Ramadhanty Nur Mishbah Hayat Rinta Kridalukmana Sukiswo Sukiswo Yudi Eko Windarto