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Pedestrian simulati...
Pedestrian simulation as multi-objective reinforcement learning
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- Ravichandran, Naresh Balaji (författare)
- KTH,Parallelldatorcentrum, PDC,Computational Brain Science Lab
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- Yang, Fangkai (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST)
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- Peters, Christopher (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST)
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- Lansner, Anders, Professor (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST)
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- Herman, Pawel, 1979- (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST)
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(creator_code:org_t)
- 2018-11-05
- 2018
- Engelska.
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Ingår i: Proceedings of the 18th International Conference on Intelligent Virtual Agents, IVA 2018. - New York, NY, USA : ACM. - 9781450360135 ; , s. 307-312
- Relaterad länk:
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https://kth.diva-por... (primary) (Raw object)
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http://kth.diva-port...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Modelling and simulation of pedestrian crowds require agents to reach pre-determined goals and avoid collisions with static obstacles and dynamic pedestrians, while maintaining natural gait behaviour. We model pedestrians as autonomous, learning, and reactive agents employing Reinforcement Learning (RL). Typical RL-based agent simulations suffer poor generalization due to handcrafted reward function to ensure realistic behaviour. In this work, we model pedestrians in a modular framework integrating navigation and collision-avoidance tasks as separate modules. Each such module consists of independent state-spaces and rewards, but with shared action-spaces. Empirical results suggest that such modular framework learning models can show satisfactory performance without tuning parameters, and we compare it with the state-of-art crowd simulation methods.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Annan teknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Other Engineering and Technologies (hsv//eng)
Nyckelord
- Agent-based simulation
- Multi-objective learning
- Parallel learning
- Reinforcement learning
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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