Complexity and individual psychology

被引:0
作者
Levin Y. [1 ]
Aharon I. [2 ]
机构
[1] Department of Philosophy, Ben-Gurion University of the Negev, P.O.B. 653, Beer-Sheva
[2] Interdisciplinary Center (IDC) Herzliya, P.O.B. 167, Herzliya
关键词
Classic cognitive science; Complexity; Computation; Connectionism; Dynamical systems theory; Embodied cognition; Representation;
D O I
10.1007/s11299-015-0171-2
中图分类号
学科分类号
摘要
In this paper we examine the question of whether complexity-like explanations can be applied to the psychology of individuals, and its implications for the scope of complexity explanations of social phenomena. We start by outlining two representational-cum-computational models of the mind—a symbolic model and a networks or connectionist one—and their pros and cons. Based on this we then outline a radical, non-representational and non-computational alternative model that has been gaining ground recently, and which has significant affinities with complexity explanations in social science. Deploying neo-Kantian considerations, we then argue that due to the discursivity, or conceptual dimension of our cognitive system, the radical alternative must be incorrect insofar as humans are concerned. Indeed, human psychology must involve, at least partly, a representational understanding of the sort provided by the symbolic model. Relatedly, we show how the discursiviry of human cognition complicates our psychology and makes it difficult to account for. Finally, we briefly address the question of how the complicated nature of individual psychology, implied by human discursivity, may affect complexity explanations of social behavior. © 2015, Springer-Verlag Berlin Heidelberg.
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页码:203 / 219
页数:16
相关论文
共 64 条
  • [1] Allen C., Bekoff M., Species of mind: the philosophy and biology of cognitive ethology, (1997)
  • [2] Anderson M.L., Embodied cognition: a field guide, Artif Intell, 149, pp. 91-130, (2003)
  • [3] Audi R., Practical reasoning and ethical decision, (2006)
  • [4] Barrett L., Beyond the brain: how body and environment shape animal and human minds, (2011)
  • [5] Bechtel W., Abrahamsen A., Connectionism and the mind: parallel processing, dynamics, and evolution in networks, (2002)
  • [6] Beer R.D., A dynamical systems perspective on agent-environment interaction, Artif Intell, 72, pp. 173-215, (1995)
  • [7] Beer R.D., Dynamical approaches to cognitive science, Trends Cognit Sci, 4, pp. 91-99, (2000)
  • [8] Beer R.D., Gallagher J.C., Evolving dynamical neural networks for adaptive behavior, Adapt Behav, 1, pp. 91-122, (1992)
  • [9] Cambrian intelligence: the early history of the new AI. MIT Press, Cambridge, pp. 133-186, (1999)
  • [10] Buchanan M., Social atoms: why the rich get richer, cheaters get caught, and your neighbor usually looks like you, (2007)