Evolution of Collective Computational Abilities of (Pre)Historic Societies - Resources
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A Special Issue was published on February 10, 2022 as a result of this workshop, available here.
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Resources
| Bibliographic Info | Link |
| H. Bhatia, G. Norgard, V. Pascucci, P. Bremer, The Helmholtz-Hodge Decomposition — A Survey. IEEE Trans. Vis. Comput. Graph. 19, 1386–1404 (2013). | Media:Bhatia2014natural.helmholtz.hodge.decomp.pdf |
| H. Bhatia, V. Pascucci, P. T. Bremer, The natural Helmholtz-Hodge decomposition for open-boundary flow analysis. IEEE Trans. Vis. Comput. Graph. 20, 1566–1578 (2014). | Media:Bhatia2013helmholtz.hodge.decomp.survey.pdf |
| R. H. Coase, The Nature of the Firm. Economica. 4, 386–405 (1937). | Media:Coase1937nature.of.the.firm.pdf |
| A. Frishman, P. Ronceray, Learning Force Fields from Stochastic Trajectories. Phys. Rev. X. 10, 21009 (2020). | Media:Frishman2020force.fields.limits.pdf |
| J. L. Garcia-Palacios, Introduction to the theory of stochastic processes and Brownian motion problems. arXiv Prepr. condmat/0701242, 1–104 (2007). | Media:Garcia.palacios2007intro.stochastic.processes.pdf |
| G. A. Johnson, in Social Archeology: Beyond Subsistence and Dating, C. L. Redman, W. T. Langhorne, M. J. Berman, N. M. Versaggi, E. V. Curtin, J. C. Wanser, Eds. (Academic Press, New York, 1978), pp. 87–105. | Media:Johnson1978InformationSources.pdf |
| G. A. Johnson, Decision-Making Organization and Pastoral Nomad Camp Size. Hum. Ecol. 11, 175–199 (1983). | Media:Johnson1984scalarstress.pdf |
| K. J. Meier, J. Bohte, Span of Control and Public Organizations: Implementing Luther Gulick’s Research Design. Public Adm. Rev. 63, 61–70 (2003). | Media:Meier2003span.control.pdf |
| J. Shin, M. H. Price, D. H. Wolpert, H. Shimao, B. Tracey, T. A. Kohler, Scale and information-processing thresholds in Holocene social evolution. Nat. Commun. 11 (2020), doi:10.1038/s41467-020-16035-9. | Media:Shin2020_scaleinformationthresholds.pdf |
| M. E. Smith. Metadata on cross‐cultural/temporal variation in civic building types by society. Prepared for the Working group, “Evolution of collective computational abilities of (pre)historic societies,” at the Santa Fe Institute, Nov 2‐4, 2020. | Media:Smith-CivicArchitecture-MetaData.pdf |
| Strang, A. Applications of the Helmholtz-Hodge Decomposition to Networks and Random Processes. (Case Western Reserve University, 2020). | Media:Strang2020hemholtzdecomp.pdf |
| G. Sugihara, R. May, H. Ye, C. H. Hsieh, E. Deyle, M. Fogarty, S. Munch, Detecting causality in complex ecosystems. Science (80-. ). 338, 496–500 (2012). | Media:Sugihara2012causality.pdf Media:Sugihara2012causality_sup.pdf |
| Y. Tong, S. Lombeyda, A. N. Hirani, M. Desbrun, Discrete multiscale vector field decomposition. ACM SIGGRAPH 2003 Pap. SIGGRAPH ’03, 445–452 (2003). | Media:Tong2012discrete.multiscale.vector.field.decomp.pdf |
| P. Turchin, T. E. Currie, H. Whitehouse, P. François et al. Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization (2017), vol. 115. | Media:Turchin2017SESHAT.pdf |
| C. Yildiz, M. Heinonen, J. Intosalmi, H. Mannerstrom, H. Lahdesmaki, Learning stochastic differential equations with Gaussian processes without gradient matching. IEEE Int. Work. Mach. Learn. Signal Process. MLSP. 2018-September (2018), doi:10.1109/MLSP.2018.8516991. | Media:Yildiz2018learning.stoch.diff.eqs.pdf |