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An online human-agent interaction system: a brain-controlled agent playing games in unity

conference contribution
posted on 2023-05-23, 14:55 authored by Cao, Z, Jie YunJie Yun
Human-agent interactions present people guide an object or agent to act as human intentions. This demonstration work develops an online human-agent interaction system, particularly targeting the brain-computer interface (BCI), which uses real-time brain cortex signals: electroencephalogram (EEG) to control the agent in Unity3D game platform. The developed system also provides the online visualisation of EEG signals, including pre-processed temporal data and power spectral in three frequency bands (theta, alpha, and beta). To build this systematic work, we firstly collect wireless EEG signals via the Bluetooth transmission from a commercially available 14-channel brainware headset (Emotiv). EEG signals are then pre-processed and fed into a trained deep learning model to predict the human intentions, which will be sent to Unity3D platform to control an agent’s movements in game playing, such as a karting game scenario. The online testing results show the feasibility of our systematic work that will benefit for human-agent interaction community. The demonstration video can be viewed at the following link: https://youtu.be/9AWKHeatc6I

History

Publication title

Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)

Pagination

1758-1760

ISBN

978-1-4503-8307-3

Department/School

School of Information and Communication Technology

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Place of publication

Richland, SC

Event title

20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)

Event Venue

London, UK

Date of Event (Start Date)

2021-05-03

Date of Event (End Date)

2021-05-07

Rights statement

Copyright 2021 International Foundation for Autonomous Agents and Multiagent Systems

Repository Status

  • Restricted

Socio-economic Objectives

Artificial intelligence

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    University Of Tasmania

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