Potential seminar topics [updated: 3. 11. 2024]

1. recreate an existing collective behaviour model that has been published fairly recently (last 5 years), and expand on that research; possible starting points (expand your research by searching for the title on http://scholar.google.com and following “cited by” and “related articles”):
• Appert-Rolland, et al. 2024. Modelling vehicle and pedestrian collective dynamics: Challenges and advancements. https://doi.org/10.48550/arXiv.2410.22896
• Itatani & Pelechano. 2024. Social Crowd Simulation: Improving Realism with Social Rules and Gaze Behavior. https://doi.org/10.1145/3677388.3696337
• Ferreira, et al. 2024. Deformable Elliptical Particles for Predictive Mesh-Adaptive Crowds. https://doi.org/10.1145/3677388.3696329
• Wu, et al. 2024. Emotion Contagion Model for Dynamical Crowd Path Planning. https://doi.org/10.53941/ijndi.2024.100014
• Hoetzlein, 2024. Flock2: A model for orientation-based social flocking. https://doi.org/10.1016/j.jtbi.2024.111880
• Bartashevich, et al. 2024. Transient Milling Dynamics in Collective Motion with Visual Occlusions. https://doi.org/10.1007/978-3-031-71533-4_12
• Castro, et al. 2024. Modeling collective behaviors from optic flow and retinal cues. https://doi.org/10.1103/PhysRevResearch.6.023016 
• Wu, et al. 2024. A Vision-Driven Model Based on Cognitive Heuristics for Simulating Subgroup Behaviors During Evacuation. https://doi.org/10.1109/TITS.2024.3421626
• Marney & Haworth, 2024. Toward comprehensive Chiroptera modeling: A parametric multiagent model for bat behavior. https://onlinelibrary.wiley.com/doi/pdf/10.1002/cav.2251
• Mohapatra & Mahapatra, 2023. Flock response to sustained asynchronous predator attacks. https://doi.org/10.1101/2023.11.14.567144
• Ruan, et al. 2023. Hawk-Pigeon Game Tactics for Unmanned Aerial Vehicle Swarm Target Defense. https://doi.org/10.1109/TII.2023.3248075
• Martinez, et al. 2023. A deep reinforcement learning strategy for autonomous robot flocking. http://doi.org/10.11591/ijece.v13i5.pp5707-5716
• Li, et al. 2023. Predator-prey survival pressure is sufficient to evolve swarming behaviors. https://doi.org/10.1088/1367-2630/acf33a 
• Puy, et al. 2023. Selective social interactions and speed-induced leadership in schooling fish. https://arxiv.org/abs/2305.17108
• Krongauz & Lazebnik 2023. Collective evolution learning model for vision-based collective motion with collision avoidance. https://doi.org/10.1371/journal.pone.0270318
• Takahashi & Komeyama 2023. Development of a feeding simulation to evaluate how feeding distribution in aquaculture affects individual differences in growth based on the fish schooling behavioral model. https://doi.org/10.1371/journal.pone.0280017
• King, et al. 2023. Biologically inspired herding of animal groups by robots. [REVIEW]. https://doi.org/10.1111/2041-210X.14049
• Cai, et al. 2023. Behavior-Based Herding Algorithm for Social Force Model Based Sheep Herd. https://doi.org/10.3390/electronics12020285
• Dachner, et al. 2023. The visual coupling between neighbours explains local interactions underlying human ‘flocking’. https://doi.org/10.1098/rspb.2021.2089
• Missila & Mahore, 2022. Emergence of intelligent collective motion in a group of agents with memory. https://arxiv.org/abs/2212.07362
• Papadopoulou, et al. 2022. Emergence of splits and collective turns in pigeon flocks under predation. https://doi.org/10.1098/rsos.211898
  
• Ranganathan, et al. 2022. Optimal shepherding and transport of a flock, https://arxiv.org/abs/2211.04352
  
• Qi, et al. 2022. The emergence of collective obstacle avoidance based on a visual perception mechanism, https://doi.org/10.1016/j.ins.2021.10.039
• Filella, et al. 2017. Hydrodynamic interactions influence fish collective behavior, https://arxiv.org/abs/1705.07821 
• Tashiro, et al. 2022. Guidance by multiple sheepdogs including abnormalities, https://doi.org/10.1007/s10015-022-00807-1
• Fujioka, et al. 2022. Shepherding Heterogeneous Flock with Model-Based Discrimination, https://arxiv.org/abs/2210.11055
• Krongauz & Lezebnik 2022. Collective Evolution Learning Model for Vision-Based Collective Motion with Collision Avoidance, https://doi.org/10.1101/2022.06.09.495429
• Hartono, et al. 2022. A Stochastic Differential Equation Model for Predator-Avoidance Fish Schooling, https://arxiv.org/abs/2210.03989
• Ivanov & Palamas. 2022. Collective Adaptation in Multi-Agent Systems: How Predator Confusion Shapes Swarm-Like Behaviors, https://arxiv.org/abs/2209.06338
• Yu, et al. 2022. Simulation of collective pursuit-evasion behavior with runtime situational awareness, https://doi.org/10.1002/cav.2124
• Cai, et al. 2022. Cooperative Driven Algorithm for Couzin Model Based Fish School by Multiple Predators, https://doi.org/10.1155/2022/4708496
• Liu, et al. 2021. Sheepdog Driven Algorithm for Sheep Herd Transport, https://doi.org/10.23919/CCC52363.2021.9549396
• Bastien & Romanczuk. 2020. A model of collective behavior based purely on vision, http://dx.doi.org/10.1126/sciadv.aay0792
• Yang, et al. 2020. A review on crowd simulation and modeling, https://doi.org/10.1016/j.gmod.2020.101081
• Collignon, et al. 2016. A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments, https://royalsocietypublishing.org/doi/10.1098/rsos.150473
• El-Fiqi, et al. 2020. A preliminary study towards an improved shepherding model, https://dl.acm.org/doi/pdf/10.1145/3377929.3390067
• Zhow, et al. 2016, Modeling of Crowd Evacuation With Assailants via a Fuzzy Logic Approach, https://doi.org/10.1109/TITS.2016.2521783
• Markowska-Kaczmar & Marcinkowski, 2020. Markov network versus recurrent neural network in forming herd behavior based on sight and simple sound communication, https://doi.org/10.1016/j.asoc.2020.106177
• Calovi, et al. 2018, Disentangling and modeling interactions in fish with burst-and-coast swimming reveal distinct alignment and attraction behaviors. https://doi.org/10.1371/journal.pcbi.1005933
• Luo, et al. 2018. ProactiveCrowd: Modelling Proactive Steering Behaviours for Agent‐Based Crowd Simulation. https://doi.org/10.1111/cgf.13303
• Xue, et al. 2017. Fuzzy Logic-Based Model That Incorporates Personality Traits for Heterogeneous Pedestrians. https://doi.org/10.3390/sym9100239
• Pearce, et al. 2014. Role of projection in the control of bird flocks. https://doi.org/10.1073/pnas.1402202111. 
• Klamser, Romanczuk. 2021. Collective predator evasion: Putting the criticality hypothesis to the test. https://doi.org/10.1371/journal.pcbi.1008832
• Davidson, et al. 2021. Collective detection based on visual information in animal groups. https://doi.org/10.1098/rsif.2021.0142  
2. a topic by a group's own choice; this should have a clear foundation based on existing research - present a 10 sentence paragraph explaining the problem that is supported by at least two scientific references.

Related literature and tools:

1. Escaping from Predators: An Integrative View of Escape Decisions, https://publicism.info/science/predators/
2. Wu W. et al. 2021. Visual information based social force model for crowd evacuation, 10.26599/TST.2021.9010023
3. Ishikawa Y. et al. 2021. Foids: bio-inspired fish simulation for generating synthetic datasets, 10.1145/3478513.3480520
4. Wolter Jolles J. et al. 2021. Both Prey and Predator Features Determine Predation Risk and Survival of Schooling Prey, 10.1101/2021.12.13.472101
5. Millington I. & Funge J. 2009. Artificial Intelligence for Games.
6. Richmond P. et al. 2023. Fast Large-Scale Agent-based Simulations on NVIDIA GPUs with FLAME GPU.