Applewhite, Timothy

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Timothy
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Timothy Applewhite

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  • Publikation
    powerGhosts & defensiveGhosts – Enhanced ghost team controller based on Ant Colony Optimization for Ms. Pac-Man
    (IEEE, 2021) Applewhite, Timothy; Kaufmann, Roger; Dornberger, Rolf; Hanne, Thomas
    This paper presents an improved controller based on Ant Colony Optimization for the ghost team of Ms. Pac-Man. The controller is an enhanced version of fairGhosts which is based on the ghostAnt framework. Various improvements were implemented in terms of parameters and concepts. Especially for the explorer ants, fairGhosts uses a simplified version, as the exact reasoning for the proposed concepts could not be determined in the ghostAnt framework. In this paper, two new types of ghost teams are proposed after the modifications were conducted: powerGhosts and defensiveGhosts. powerGhosts take into account the power pill aspect for stopping criteria and solution quality of the explorer ants, and defensiveGhosts additionally involve a threshold of Ms. Pac-Man’s distance to the nearest power pill for the hunter ants, so as not to be caught easily. Test results show that the powerGhosts version shows on average 15% better results than the initial fairGhosts setup, while defensiveGhosts performs equal or slightly worse than the initial implementation. It can be concluded that including the power pill aspect in the explorer ants concept shows an improved performance of the ghost team. On the other hand, the concept of distancing ghosts from Ms. Pac-Man when she is near a power pill did not result in any significant improvement.
    04B - Beitrag Konferenzschrift
  • Publikation
    Novel bidirectional multimodal system for affective human-robot engagement
    (IEEE, 2021) Applewhite, Timothy; Zhong, Jia; Dornberger, Rolf
    Multimodal interaction is an essential prerequisite for affective human-robot engagement. Research on bidirectional, affective multimodal interaction systems investigates systems that recognize a user's affect and generate emotional response based on this user's affect. The presented work investigates a novel bidirectional, affective multimodal interaction system using a social robot and an open-source dialogue system framework, developing a prototype based here on Pepper and Rasa. Compared to special lab robotics systems, the proposed system is more attainable, while incorporating, alongside speech and facial expression, eye gaze as one of the major features to convey emotions as input channels. The system generates and emulates emotional output behaviors based on a user's affect using speech, gestures and emojis. This paper describes the concrete implementation and evaluation of the proposed system. Results of the evaluation show that, although the recognition accuracy of the input channels perform differently well, the system can derive well-defined rule-based emotional output behaviors with a high multimodal accuracy rate in the given test scenarios.
    04B - Beitrag Konferenzschrift