TY - GEN
T1 - A bio-inspired artificial agent to complete a herding task with novices
AU - Nalepka, Patrick
AU - Lamb, Maurice
AU - Kallen, Rachel W.
AU - Shockley, Kevin
AU - Chemero, Anthony
AU - Richardson, Michael J.
N1 - Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
PY - 2016/9
Y1 - 2016/9
N2 - Models of robust human-human coordination can guide the design of adaptive and responsive human-robot systems. Here we test an artificial agent that embodies low- dimensional nonlinear dynamic equations derived from human behavior while completing a two-agent herding task, where the goal is to contain reactive spheres to the center of a target region. The model was able to complete the task alongside human novices in a virtual version of the experimental setup used in Nalepka and colleagues (submitted). Not only did the model lead participants to successful performance, but also 12 out of 18 participants reported that they believed their partner was a human participant in another room. The model was therefore able to capture the complex social behavior that defined robust task success in terms of lower dimensional dynamical equations that characterizes the emergent behavioral dynamics of embedded multiagent behavior.
AB - Models of robust human-human coordination can guide the design of adaptive and responsive human-robot systems. Here we test an artificial agent that embodies low- dimensional nonlinear dynamic equations derived from human behavior while completing a two-agent herding task, where the goal is to contain reactive spheres to the center of a target region. The model was able to complete the task alongside human novices in a virtual version of the experimental setup used in Nalepka and colleagues (submitted). Not only did the model lead participants to successful performance, but also 12 out of 18 participants reported that they believed their partner was a human participant in another room. The model was therefore able to capture the complex social behavior that defined robust task success in terms of lower dimensional dynamical equations that characterizes the emergent behavioral dynamics of embedded multiagent behavior.
UR - http://alife2016.alife.org/
UR - https://mitpress.mit.edu/books/proceedings-artificial-life-conference-2016
UR - http://www.scopus.com/inward/record.url?scp=85087107209&partnerID=8YFLogxK
U2 - 10.7551/978-0-262-33936-0-ch104
DO - 10.7551/978-0-262-33936-0-ch104
M3 - Conference proceeding contribution
AN - SCOPUS:85087107209
T3 - Complex Adaptive Systems
SP - 656
EP - 663
BT - Proceedings of the Artificial Life Conference 2016
A2 - Gershenson, Carlos
A2 - Froese, Tom
A2 - Siqueiros, Jesus M.
A2 - Aguilar, Wendy
A2 - Izquierdo, Eduardo J.
A2 - Sayama, Hiroki
PB - MIT Press
CY - London
T2 - International Conference on the Synthesis and Simulation of Living Systems (15th : 2016)
Y2 - 4 July 2016 through 8 July 2016
ER -