Simulating collective transport of virtual ants

Authors: Zhang, J.

http://eprints.bournemouth.ac.uk/29461/

Journal: Computer Animation & Virtual Worlds

Volume: 28

Issue: 3-4

Publisher: John Wiley & Sons Inc.

ISSN: 1546-4261

DOI: 10.1002/cav.1779

Guo, SH; Wang, ML; Notman, G; Chang, J; Zhang, JJ; Liao, MH

This data was imported from Scopus:

Authors: Guo, S., Wang, M., Notman, G., Chang, J., Zhang, J. and Liao, M.

http://eprints.bournemouth.ac.uk/29461/

Journal: Computer Animation and Virtual Worlds

Volume: 28

Issue: 3-4

eISSN: 1546-427X

ISSN: 1546-4261

DOI: 10.1002/cav.1779

Copyright © 2017 John Wiley & Sons, Ltd. This paper simulates the behaviour of collective transport where a group of ants transports an object in a cooperative fashion. Different from humans, the task coordination of collective transport, with ants, is not achieved by direct communication between group individuals, but through indirect information transmission via mechanical movements of the object. This paper proposes a stochastic probability model to model the decision-making procedure of group individuals and trains a neural network via reinforcement learning to represent the force policy. Our method is scalable to different numbers of individuals and is adaptable to users' input, including transport trajectory, object shape, external intervention, etc. Our method can reproduce the characteristic strategies of ants, such as realign and reposition. The simulations show that with the strategy of reposition, the ants can avoid deadlock scenarios during the task of collective transport.

This data was imported from Web of Science (Lite):

Authors: Guo, S., Wang, M., Notman, G., Chang, J., Zhang, J. and Liao, M.

http://eprints.bournemouth.ac.uk/29461/

Journal: COMPUTER ANIMATION AND VIRTUAL WORLDS

Volume: 28

Issue: 3-4

eISSN: 1546-427X

ISSN: 1546-4261

DOI: 10.1002/cav.1779

The data on this page was last updated at 04:50 on December 18, 2018.