Modeling the Behavioral Dynamics of Social Action and Coordination

A fundamental feature of social behavior is face-to-face, co-present interaction. The success of such interactions, whether measured in terms of social connection, goal achievement, or the ability of an individual or group of individuals to know and predict the meaningful intentions and behaviors of others, is not only dependent on the neural and representational processes of social cognition and perception, but also on the physical (environmental) and perceptual-motor processes that make such face-to-face and co-present interaction possible. A primary goal of my research program is to model the complex dynamics of such goal-directed social and multi-agent activity, in an attempt to explain how the dynamics of such behavioral activity is an emergent and self-organized consequence of the complex interactions that exist between physical, neural, informational, and social properties. This involves developing dynamical and computational models of the temporal and spatial patterns of social interaction and coordination across a wide range of prototypical social and multi-agent behaviors.

SELECT PUBLICATIONS:

Patil, G., Nalepka, P., Kallen, R. W., & Richardson, M. J. (2020). Hopf Bifurcations in Complex Multiagent Activity: The Signature of Discrete to Rhythmic Behavioral Transitions. Brain Sciences, 10(8), 536.

Rigoli, L. M., Lorenz, T., Coey, C., Kallen, R., Jordan, S., & Richardson, M. J. (2020). co-actors exhibit Similarity in their Structure of Behavioural Variation that Remains Stable Across Range of naturalistic Activities. Scientific reports, 10(1), 1-11.

Chauvigné, L. A., Walton, A., Richardson, M. J., & Brown, S. (2019). Multi-person and multisensory synchronization during group dancing. Human movement science, 63, 199-208.

Walton, A., Washburn, A., Langland-Hassan, P., Chemero, A., Kloos, H., & Richardson, M. J. (2018). Creating time: social collaboration in music improvisation. Topics in Cognitive Science, 10, 95-119.

Kijima, A., Shima, H., Okumura, M., Yamamoto, Y., & Richardson, M. J. (2017) Effects of Agent-Environment Symmetry on the coordination dynamics of triadic jumping. Frontiers in Cognitive Science. 8:3. doi: 10.3389/fpsyg.2017.00003.

Lamb, M., Kallen, R. W., Harrison, S. J., Di Bernardo, M., Minai, A., & Richardson, M. J. (2017). To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task. Frontiers in Psychology, 8

Nalepka, P., Kallen, R. W., Chemero, A., Saltzman, E., & Richardson, M .J. (2017). Herd Those Sheep: Emergent multiagent coordination and behavioral mode switching. Psychological Science. DOI: 10.1177/0956797617692107.

Richardson, M., Kallen, R., Nalepka, P., Harrison, S., Lamb, M., Chemero, A., Saltzman, E. and Schmidt, R. (2016). Modeling Embedded Interpersonal and Multiagent Coordination. In Proceedings of the 1st International Conference on Complex Information Systems (COMPLEXIS 2016), pp.155-164.

Richardson, M. J., Harrison, S. J., Kallen, R. W., Walton, A., Eiler, B., & Schmidt, R. C. (2015). Self-Organized Complementary Coordination: Dynamics of an Interpersonal Collision-Avoidance Task. Journal of Experimental Psychology: Human Perception and Performance. 41, 665-79.

Richardson, M. J., & Kallen, R. W. (2015). Symmetry-Breaking and the Contextual Emergence of Human Multiagent Coordination and Social Activity. In E. Dzhafarov, S. Jordan, R. Zhang, and V. Cervantes (Eds.). Contextuality from Quantum Physics to Psychology. (pp. 229-286). World Scientific.