Modelling Human Perceptual-Motor Interaction for Human-Machine Applications

Research output

Research output per year 2019 2021 2022 2023 2025

• 14 Article
• 8 Conference proceeding contribution
• 1 Conference paper
• 1 Review article

Research output per year

Research output per year

Search results

• 2025

  Human-inspired strategies for controlling swarm systems

  Nalepka, P., Patil, G., Kallen, R. W. & Richardson, M. J., 30 Jan 2025, In: Philosophical Transactions of the Royal Society A. 383, 2289, p. 1-14 14 p., 20240147.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  1 Citation (Scopus)

  27 Downloads (Pure)
• 2024

  Autistic young people adaptively use gaze to facilitate joint attention during multi-gestural dyadic interactions

  Caruana, N., Nalepka, P., Perez, G. A., Inkley, C., Munro, C., Rapaport, H., Brett, S., Kaplan, D. M., Richardson, M. J. & Pellicano, E., Jun 2024, In: Autism. 28, 6, p. 1565–1581 17 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Ocular Fixation 100%
  • interaction 64%
  • Interpersonal Relations 54%
  • Virtual Reality 42%
  • Hand 39%
  2 Citations (Scopus)

  51 Downloads (Pure)

• Kinematics in context: predicting other's action intentions entails the perception of affordances

  Alhasan, A., Karin, E., Caruana, N., Cross, E., Kaplan, D. & Richardson, M. J., Jul 2025, In: Cognition. 260, p. 1-13 13 p., 106122.

  Research output: Contribution to journal › Article › peer-review

  File
  49 Downloads (Pure)

• Modelling human navigation and decision dynamics in a first-person herding task

  bin Kamruddin, A., Sandison, H., Patil, G., Musolesi, M., di Bernardo, M. & Richardson, M. J., Oct 2024, In: Royal Society Open Science. 11, 10, p. 1-21 21 p., 231919.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File
  3 Citations (Scopus)

  16 Downloads (Pure)
• 2023

  Behavioral dynamics of conversation, (mis)communication and coordination in noisy environments

  Miles, K., Weisser, A., Kallen, R. W., Varlet, M., Richardson, M. J. & Buchholz, J. M., 20 Nov 2023, In: Scientific Reports. 13, 1, p. 1-14 14 p., 20271.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Noise 100%
  • Communication 81%
  • Restaurants 23%
  • Sitting Position 18%
  • Hearing 16%
  8 Citations (Scopus)

  107 Downloads (Pure)

• Dynamical biomarkers in teams and other multiagent systems

  Patil, G., Nalepka, P., Novak, A., Auletta, F., Pepping, G-J., Fransen, J., Kallen, R. W. & Richardson, M. J., Jun 2023, In: Journal of Science and Medicine in Sport. 26, S1, p. S9-S13 5 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Sports 100%
  • Biomarkers 74%
  • Acceleration 55%
  • Decision Making 46%
  2 Citations (Scopus)

  99 Downloads (Pure)

• Incidental coupling of perceptual-motor behaviors associated with solution insight during physical collaborative problem-solving

  Nalepka, P., O'Connor, F., Kallen, R. W. & Richardson, M. J., 2023, Proceedings of the 45th Annual Conference of the Cognitive Science Society. Goldwater, M., Anggoro, F. K., Hayes, B. K. & Ong, D. C. (eds.). Seattle, WA: Cognitive Science Society, p. 325-332 8 p. (Annual Conference of the Cognitive Science Society; vol. 45).

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  Open Access

  File

  • Scaffolds 100%
  86 Downloads (Pure)

• Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-AI

  Auletta, F., Kallen, R. W., di Bernardo, M. & Richardson, M. J., 27 Mar 2023, In: Scientific Reports. 13, 1, p. 1-14 14 p., 4992.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Supervised Machine Learning 100%
  • Artificial Intelligence 83%
  • Long-Term Memory 48%
  • Joints 44%
  • Short-Term Memory 39%
  7 Citations (Scopus)

  83 Downloads (Pure)

• Scaffolding deep reinforcement learning agents using dynamical perceptual-motor primitives

  Patil, G., Nalepka, P., Stening, H. F., Kallen, R. W. & Richardson, M. J., 2023, Proceedings of the 45th Annual Conference of the Cognitive Science Society. Goldwater, M., Anggoro, F. K., Hayes, B. K. & Ong, D. C. (eds.). Seattle, WA: Cognitive Science Society, p. 1981-1989 9 p. (Annual Conference of the Cognitive Science Society; vol. 45).

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  Open Access

  File

  • Decision making 12%
  100 Downloads (Pure)
• 2022

  A comparison of dynamical perceptual-motor primitives and deep reinforcement learning for human-artificial agent training systems

  Rigoli, L., Patil, G., Nalepka, P., Kallen, R. W., Hosking, S., Best, C. & Richardson, M. J., Jun 2022, In: Journal of Cognitive Engineering and Decision Making. 16, 2, p. 79–100 22 p.

  Research output: Contribution to journal › Article › peer-review

  • Deep Learning 100%
  • Psychology Reinforcement 78%
  • reinforcement 70%
  • expert 36%
  • performance 26%
  5 Citations (Scopus)

• Assessing team effectiveness by how players structure their search in a first-person multiplayer video game

  Nalepka, P., Prants, M., Stening, H., Simpson, J., Kallen, R. W., Dras, M., Reichle, E. D., Hosking, S. G., Best, C. & Richardson, M. J., Oct 2022, In: Cognitive Science. 46, 10, p. 1-32 32 p., e13204.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Video Games 100%
  • computer game 74%
  • Redundancy 63%
  • Personnel 57%
  • human being 39%
  4 Citations (Scopus)

  75 Downloads (Pure)

• Conversation dynamics in a multiplayer video game with knowledge asymmetry

  Simpson, J., Nalepka, P., Kallen, R. W., Dras, M., Reichle, E. D., Hosking, S. G., Best, C., Richards, D. & Richardson, M. J., 3 Nov 2022, In: Frontiers in Psychology. 13, p. 1-16 16 p., 1039431.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Video Games 100%
  • asymmetry 75%
  • computer game 74%
  • conversation 57%
  • Communication 37%
  4 Citations (Scopus)

  132 Downloads (Pure)

• Evaluating human-artificial agent decision congruence in a coordinated action task

  Patil, G., Bagala, P., Nalepka, P., Kallen, R. W. & Richardson, M. J., 5 Dec 2022, HAI 2022: Proceedings of the 10th Conference on Human-Agent Interaction. New York, NY: Association for Computing Machinery, Inc, p. 327-329 3 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  • Recommender systems 100%
  • Decision making 36%
  1 Citation (Scopus)

• Neurodiverse human-machine interaction and collaborative problem-solving in social VR

  Nalepka, P., Caruana, N., Kaplan, D. M., Kallen, R. W., Pellicano, E. & Richardson, M. J., 2022, HAI 2022: Proceedings of the 10th Conference on Human-Agent Interaction. New York, NY: Association for Computing Machinery, p. 293-295 3 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  • Virtual reality 100%
  • Experiments 13%
• 2021

  Dynamical perceptual-motor primitives for better deep reinforcement learning agents

  Patil, G., Nalepka, P., Rigoli, L., Kallen, R. W. & Richardson, M. J., 2021, Advances in practical applications of agents, multi-agent systems, and social good: the PAAMS collection : 19th international conference, PAAMS 2021, Salamanca, Spain, October 6-8, 2021 : proceedings. Dignum, F., Corchado, J. M. & De La Prieta, F. (eds.). Cham, Switzerland: Springer, Springer Nature, p. 176–187 12 p. (Lecture notes in artificial intelligence; no. 12946).

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  • Reinforcement Learning 100%
  • Human Behavior 42%
  • Actors 39%
  • Human 34%
  • Artificial Intelligence 34%
  5 Citations (Scopus)

• Human-inspired strategies to solve complex joint tasks in multi agent systems

  Auletta, F., di Bernardo, M. & Richardson, M. J., Sept 2021, In: IFAC-PapersOnLine. 54, 17, p. 105-110 6 p.

  Research output: Contribution to journal › Conference paper › peer-review

  Open Access

  File

  • Multi agent systems 100%
  • Machine learning 77%
  • Computer simulation 57%
  5 Citations (Scopus)

  71 Downloads (Pure)

• Interaction flexibility in artificial agents teaming with humans

  Nalepka, P., Gregory-Dunsmore, J. P., Simpson, J., Patil, G. & Richardson, M., 2021, CogSci 2021: program for the 43rd Annual Meeting of the Cognitive Science Society: comparative cognition, animal minds. Seattle, WA: Cognitive Science Society, p. 112-118 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  • Cognitive Science 100%
  • Deep Learning 90%
  • Psychology Reinforcement 70%
  • Autonomous agents 60%
  • Direction compound 47%
  8 Citations (Scopus)

• Navigational behavior of humans and deep reinforcement learning agents

  Rigoli, L. M., Patil, G., Stening, H. F., Kallen, R. W. & Richardson, M. J., 22 Sept 2021, In: Frontiers in Psychology. 12, p. 1-15 15 p., 725932.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Deep Learning 100%
  • Psychology Reinforcement 78%
  • reinforcement 70%
  • learning 24%
  • learning behavior 13%
  1 Citation (Scopus)

  110 Downloads (Pure)

• Synchronous vs. non-synchronous imitation: using dance to explore interpersonal coordination during observational learning

  Crone, C., Rigoli, L., Patil, G., Pini, S., Sutton, J., Kallen, R. W. & Richardson, M., Apr 2021, In: Human Movement Science. 76, p. 1-19 19 p., 102776.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • imitation 100%
  • dance 93%
  • Learning 65%
  • Psychological Practice 46%
  • performance 41%
  12 Citations (Scopus)

  80 Downloads (Pure)

• Task dynamics define the contextual emergence of human corralling behaviors

  Nalepka, P., Silva, P. L., Kallen, R. W., Shockley, K., Chemero, A., Saltzman, E. & Richardson, M. J., 15 Nov 2021, In: PLoS ONE. 16, 11, p. 1-21 21 p., e0260046.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Animals 100%
  • Locomotion 96%
  • Aptitude 67%
  14 Citations (Scopus)

  56 Downloads (Pure)
• 2020

  Employing models of human social motor behavior for artificial agent trainers

  Rigoli, L. M., Nalepka, P., Douglas, H., Kallen, R. W., Hosking, S., Best, C., Saltzman, E. & Richardson, M., 2020, AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems. An, B., Yorke-Smith, N., El Fallah Seghrouchni, A. & Sukthankar, G. (eds.). Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), p. 1134-1142 9 p. (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS; vol. 2020-May).

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  • Personnel 100%
  • Costs 50%
  • Experiments 46%
  13 Citations (Scopus)

• Hopf bifurcations in complex multiagent activity: the signature of discrete to rhythmic behavioral transitions

  Patil, G., Nalepka, P., Kallen, R. W. & Richardson, M. J., Aug 2020, In: Brain Sciences. 10, 8, p. 1-18 18 p., 536.

  Research output: Contribution to journal › Review article › peer-review

  Open Access

  File

  • Learning 100%
  13 Citations (Scopus)

  55 Downloads (Pure)
• 2019

  A hierarchical behavioral dynamic approach for naturally adaptive human-agent pick-and-place interactions

  Lamb, M., Nalepka, P., Kallen, R. W., Lorenz, T., Harrison, S. J., Minai, A. A. & Richardson, M. J., 2019, In: Complexity. 2019, p. 1-16 16 p., 5964632.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Human robot interaction 100%
  • Dynamic models 34%
  • Glass 34%
  • Robotics 32%
  12 Citations (Scopus)

  77 Downloads (Pure)

• Practical applications of multiagent shepherding for human-machine interaction

  Nalepka, P., Kallen, R. W., Chemero, A., Saltzman, E. & Richardson, M. J., 2019, Advances in practical applications of survivable agents and multi-agent systems: The PAAMS Collection - 17th International Conference, PAAMS 2019, Proceedings. Demazeau, Y., Matson, E., Corchado, J. M. & De la Prieta, F. (eds.). Switzerland: Springer, Springer Nature, p. 168-179 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11523 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

  • Human-machine Interaction 100%
  • Human 44%
  • Autonomous agents 15%
  • Multi agent systems 11%
  • Autonomous Agents 10%
  7 Citations (Scopus)