Publications

Publications

GSO trends are discussed in

M. Prokopenko and C. Gershenson, Entropy Methods in Guided Self-Organisation, Entropy, special issue on Entropy Methods in Guided Self-Organization, 16(10), 5232-5241, 2014.
Guided Self-Organization: Inception, M. Prokopenko (ed)., Springer, 2014.
D. Polani, M. Prokopenko, L. S. Yaeger, Information and Self-Organization of Behavior, Advances in Complex Systems, topical issue on Guided Self-Organisation, 16(2): 1303001-1-1303001-12, 2013.
N. Ay, R. Der, M. Prokopenko, Guided Self-Organization: Perception-Action Loops of Embodied Systems, Theory in Biosciences, special issue on Guided Self-Organisation (GSO-2010), 131: 125–127, 2012.
M. Prokopenko. Guided self-organization, HFSP Journal, 3(5), 287-289, DOI: 10.2976/1.3233933, 2009.

Selected papers of GSO-2008 were published by the Human Frontier Science Program (HFSP) Journal, in the Special Issue on Guided Self-Organization.
A special issue of Theory in Biosciences followed with selected papers from GSO-2009.
Selected papers from GSO-2010 and GSO-2011 were published in a topical issue of Advances in Complex Systems.
A special issue in the Entropy journal comprised selected papers from GSO-2013.
The book "Guided Self-Organisation: Inception" was published in 2014 by Springer.
Following GSO-2014, a research topic "Theory and Applications of Guided Self-Organisation in Real and Synthetic Dynamical Systems" was published in Computational Intelligence section of Frontiers Robotics and AI during 2015 and 2016.
Frontiers in Robotics and AI has also run two GSO-related research topics in 2019-2020: Complexity and Self-Organization and Designing Self-Organization in the Physical Realm
A workshop on "Evolution of Social Complexity" explored several related topics in 2020.

See below for more publications...

B. P. Evans, M. Prokopenko, A maximum entropy model of bounded rational decision-making with prior beliefs and market feedback, Entropy, 23(6), 669, 2021.
N. E. Carey, P. Bardunias, R. Nagpal, J. Werfel, Validating a termite-inspired construction coordination mechanism using an autonomous robot, Frontiers in Robotics and AI, doi.org/10.3389/frobt.2021.645728, 2021.
C. Gershenson, V. Trianni, J. Werfel, H. Sayama, Self-organization and Artificial Life, Artificial Life, 26 (3): 391–408, 2020.
N. C. Volpi, D. Polani, Goal-directed empowerment: Combining intrinsic motivation and task-oriented behaviour, IEEE Transactions on Cognitive and Developmental Systems, doi: 10.1109/TCDS.2020.3042938, 2020.
N. Harding, R. E. Spinney, M. Prokopenko, Population mobility induced phase separation in SIS epidemic and social dynamics, Scientific Reports, 10: 7646, 2020.
E. Crosato, M. Prokopenko, R. E. Spinney, Irreversibility and emergent structure in active matter, Physical Review E, 100, 042613, 2019.
S. Blaes, M. Vlastelica, J. Zhu, G. Martius, Control what you can: Intrinsically motivated task-planning agent, in Neural Information Processing (NeurIPS’19), 12520-12531, Curran Associates, Inc., NeurIPS'19, 2019.
M. Prokopenko, M. Harré, J. Lizier, F. Boschetti, P. Peppas, S. Kauffman, Self-referential basis of undecidable dynamics: from the Liar paradox and the halting problem to the edge of chaos, Physics of Life Reviews, 31, 134-156, 2019.
Biehl, M., Guckelsberger, C., Salge, C., Smith, S. and Polani, D. Expanding the active inference landscape: More intrinsic motivations in the perception-action loop, Frontiers in Neurorobotics, 12, 45, 2018.
Crosato E., Jiang L., Lecheval, V., Lizier, J. T., Wang, X. R., Tichit, P., Theraulaz, G. and Prokopenko, M. Informative and misinformative interactions in a school of fish, Swarm Intelligence, 2018.
Crosato, E., Spinney, R. E., Nigmatullin, R., Lizier, J. T. and Prokopenko, M. Thermodynamics and computation during collective motion near criticality, Physical Review E, 97 (1), 012120, 2018.
Kalloniatis, A. C., Zuparic, M. L. and Prokopenko, M. Fisher Information and criticality in the Kuramoto model of nonidentical oscillators, Physical Review E, 98 (2), 022302, 2018.
Melenbrink, N. and Werfel, J. Local force cues for strength and stability in a distributed robotic construction system, Swarm Intelligence, 12(2): 129-153, 2018.
Biehl, M. and Polani, D. Action and perception for spatiotemporal patterns, C. Knibbe et al, eds., Proceedings of the ECAL 2017, Lyon, France, 4-8 September 2017, Cambridge, MA: The MIT Press, 2017.
Carreón, G., Gershenson, C., and Pineda, L. A. Improving public transportation systems with self-organization: A headway-based model and regulation of passenger alighting and boarding, PLOS ONE, 12(12):1–20, 2017.
Prokopenko, M. Modelling complex systems and guided self-organisation, Journal and Proceedings of the Royal Society of New South Wales, 150, 463/464, 104-109, 2017.
Robu, A. D., Salge, C., Nehaniv, C. L. and Polani, D. Time as it could be measured in artificial living systems, C. Knibbe et al, eds., Proceedings of the ECAL 2017, Lyon, France, 4-8 September 2017, Cambridge, MA: The MIT Press, 2017.
Zapotecatl, J. L., Rosenblueth, D. A. and Gershenson, C. Deliberative self-organizing traffic lights with elementary cellular automata, Complexity, 2017:7691370, 2017.
Ghazi-Zahedi, K., Haeufle, D. F. B., Montúfar, G., Schmitt, S. and Ay, N. Evaluating morphological computation in muscle and DC-motor driven models of hopping movements, Frontiers in robotics and AI, 3:42, 2016.
Perrone, P. and Ay, N. Hierarchical quantification of synergy in channels, Frontiers in Robotics and AI, 2:35, 2016.
Spinney, R. E., Lizier, J. T. and Prokopenko, M. Transfer entropy in physical systems and the arrow of time, Physical Review E, 94, 022135, 2016.

Virágh, C., Nagy, M., Gershenson, C. and Vásárhelyi, G. Self-organized UAV traffic in realistic environments, In Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, pages 1645–1652. IEEE, Daejeon, South Korea, 2016.
Gershenson, C. and Helbing, D. When slower is faster, Complexity, 21(2):9–15, 2015.
Kasthurirathna, D. and Piraveenan, M. Emergence of scale-free characteristics in socio-ecological systems with bounded rationality, Scientific Reports, 5:10448, 2015.
Prokopenko, M., Barnett, L., Harré, M., Lizier, J. T., Obst, O. and Wang, X. R. Fisher Transfer Entropy: Quantifying the gain in transient sensitivity, Phil. Trans. R. Soc. A, vol. 471(2184), 20150610, 2015.
Prokopenko, M. and Einav, I. Information thermodynamics of near-equilibrium computation, Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 91(6), 1-8, 2015.
Salge, C., Ay, N., Polani, D. and Prokopenko, M. Zipf's Law: Balancing Signal Usage Cost and Communication Efficiency, PLOS ONE, 10(10): e0139475, 2015.

Wibral, M., Lizier, J. T. and Priesemann, V. Bits from Biology for Biologically-inspired Computing, Frontiers in Robotics and AI, 2(5), 2015.
Harré, M. and Bossomaier, T. Strategic islands in economic games: Isolating economies from better outcomes, Entropy, 16(9), 5102-5121, 2014.
Kasthurirathna, D., Piraveenan, M. and Harré, M. Influence of topology in the evolution of coordination in complex networks under information diffusion constraints, European Physical Journal B, 87(1), 1-15, 2014.
Prokopenko, M. and Lizier, J. T. Transfer Entropy and Transient Limits of Computation, Scientific Reports, 4:5394, 2014.

Werfel, J., Petersen K. and Nagpal, R. Designing collective behavior in a termite-inspired robot construction team, Science, 343(6172): 754-758, 2014.

Barnett, L., Lizier, J. T., Harré, M., Seth, A. K. and Bossomaier, T. Information flow in a kinetic Ising model peaks in the disordered phase, Physical Review Letters, 111(17), 177203, 2013. Also see: Supplementary material.