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SUMMARY:CS MSc Thesis Presentation 8 September 2026
DESCRIPTION:Kontakt: birger.swahn@cs.lth.se\n\nTuesday\, 8 September there 
 will be a master thesis presentation in Computer Science at Lund Universit
 y\, Faculty of Engineering.The presentation will take place in E:4130 (Luc
 as).Note to potential opponents: Register as an opponent to the presentati
 on of your choice by sending an email to the examiner for that presentatio
 n (firstname.lastname@cs.lth.se). Do not forget to specify the presentatio
 n you register for! Note that the number of opponents may be limited (ofte
 n to two)\, so you might be forced to choose another presentation if you r
 egister too late. Registrations are individual\, just as the oppositions a
 re! More instructions for opponents are found here on the LTH thesis proje
 ct page.11:00-12:00 in E:4130 (Lucas)Presenter: Tianci WangTitle: Learning
  Context-Aware Guidance Behaviors for Inclusive Museum RobotsExaminer: Jac
 ek MalecSupervisors: Davide Tateo (LTH)\, Andrea Bonarini (Politecnico di 
 Milano)Human-robot interaction aims to enable robots to respond appropriat
 ely to people. In museums\, guide robots lead visitors through tours\, whe
 re changing visitor states may require different guidance behaviours. This
  thesis investigates whether reinforcement learning can improve museum rob
 ot guidance while balancing visitor needs and tour efficiency. We modelled
  a museum environment and visitor dynamics in MuJoCo. Visitor motion follo
 ws a Social Force Model combining goal-directed movement with interactions
  from nearby people\, the robot\, and the environment. During tours\, visi
 tors follow the robot and listen to explanations. Human states of distract
 ion\, impatience\, and overwhelm are inferred using fuzzy logic from tempo
 ral and spatial factors. Robot uses predefined guidance behaviours\, while
  reinforcement learning optimizes their control parameters. Different algo
 rithms are compared with a fixed baseline. Results show that the optimized
  strategies shorten tour duration and reduce all three negative visitor st
 ates\, highlighting the potential of reinforcement learning for adaptive m
 useum guide robots.&nbsp\;\n\nMer information om händelsen: https://www.c
 s.lth.se/evenemang/cs-msc-thesis-presentation-8-september-2026
DTSTART;TZID=GMT:20260908T090000
DTEND;TZID=GMT:20260908T100000
LOCATION:E:4130 (Lucas)
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