Using Markov Decision Process to Model Deception for Robotic and Interactive Game Applications

被引：0

作者：

Ayub, Ali ^{[1
]}

Morales, Aldo ^{[2
]}

Banerjee, Amit ^{[3
]}

机构：

[1] Penn State Univ, Dept Elect Engn, State Coll, PA 16802 USA

[2] Penn State Harrisburg, Dept Elect Engn, Middletown, PA 17057 USA

[3] Penn State Harrisburg, Dept Mech Engn, Middletown, PA 17057 USA

来源：

2021 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE) | 2021年

关键词：

Human-Computer Interaction (HCI); Robotics; Deception; Interactive Gaines;

D O I：

10.1109/ICCE50685.2021.9427633

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper investigates deception in the context of motion using a simulated mobile robot. We analyze some previously designed deceptive strategies on a mobile robot simulator. We then present a novel approach to adaptively choose target-oriented deceptive trajectories to deceive humans for multiple interactions. Additionally, we propose a new metric to evaluate deception on data collected from the users when interacting with the mobile robot simulator. We performed a user study to test our proposed adaptive deceptive algorithm, which shows that our algorithm deceives humans even for multiple interactions and it is more effective than random choice of deceptive strategies.

引用

页数：6

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