Abstract
Although computational models of cognitive agents that incorporate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is explored, through simulating survival strategies of tribal societies. The results of the simulation demonstrate interactions between cognitive and social factors. For example, we show that cognitive capabilities and tendencies may be relevant to what social institutions may be adopted. This work points to a cognitively based approach towards social simulation, as well as a new area of research—exploring the cognitive–social interaction through cognitively based social simulation.
Similar content being viewed by others
Notes
These tasks include serial reaction time tasks, artificial grammar learning tasks, process control tasks, categorical inference tasks, alphabetical arithmetic tasks, and the Tower of Hanoi task (see, e.g., Sun 2002). In addition, extensive work has been done on a complex minefield navigation task (Sun et al. 2001). Simulations involving motivational structures and metacognitive processes are also under way.
Due to running-time considerations, the specialization threshold is held constant in all simulations reported here.
This method is also known as Luce’s choice axiom (Watkins 1989). It is found to match psychological data in many domains.
Note that our simulation so far did not deal with the evolution of cognitive attributes, such as learning rate and so on, which should be tackled in future work.
Note that in this work, we did not deal with the evolution of social institutions in a substantive way. This issue should be tackled in future.
But again, our simulation so far did not deal with the evolution of certain important cognitive attributes, such as learning rate and so on.
For example, in CLARION, the cognitive parameters that might be evolved include learning rate, probability of using the bottom level, and so on.
References
Alexander J, Giesen B, Munch R, Smelser N (eds) (1987) The micro–macro link. University of California Press, Berkeley
Atran S, Norenzayan A (2003) Religion’s evolutionary landscape: counterintuition, commitment, compassion, and communion. Brain Behav Sci (in press)
Axelrod R (1984) The evolution of cooperation. Basic Books, New York
Bar-Yam Y (1997) Dynamics of complex systems. Perseus Books, New York
Bourdieu P, Wacquant L (1992) An invitation to reflexive sociology. University of Chicago Press, Chicago
Boyer P, Ramble C (2001) Cognitive templates for religious concepts: cross-cultural evidence for recall of counter-intuitive representations. Cogn Sci 25:535–564
Camerer C (1997) Progress in behavioral game theory. J Econ Perspect 11(4):167–188
Carley K, Newell A (1994) The nature of social agent. J Math Sociol 19(4):221–262
Castelfranchi C (2001) The theory of social functions: challenges for computational social science and multi-agent learning. In: Ron Sun (ed) Cognitive systems research, special issue on the multi-disciplinary studies of multi-agent learning 2(1):5–38
Cecconi F, Parisi D (1998) Individual versus social survival strategies. J Artif Soc Soc Simul 1(2) http://www.soc.surrey.ac.uk/JASSS/1/2/1.html
Conte R, Castelfranchi C (1995) Understanding the effects of norms in social groups through simulation. In: Gilbert N, Conte R (eds) Artificial societies: the computer simulation of social life. UCL Press, London
Cosmides L, Tooby J (1994) Beyond intuition and instinct blindness: toward an evolutionarily rigorous cognitive science. Cognition 50:41–77
Doran J, Palmer M (1995) The EOS project: integrating two models of Palaeolithic social change. In: Gilbert N, Conte R (eds) Artificial societies. UCL Press, London
Doran J, Palmer M, Gilbert N, Mellars P (1994) The EOS project: modeling upper Palaeolithic social change. In: Gilbert N, Doran J (eds) Simulating societies. UCL Press, London
Durkheim W (1895/1962) The rules of the sociological method. The Free Press, Glencoe
Gilbert N (1995) Simulation: an emergent perspective. In: Conference on new technologies in the social sciences. Bournemouth, UK
Gray W, Altmann E (2001) Cognitive modeling and human–computer interaction. In: Karwowski W (ed) International encyclopedia of ergonomics and human factors. Taylor and Francis, New York 1:387–391
Hutchins E (1995) How a cockpit remembers its speeds. Cogn Sci 19:265–288
Kahan J, Rapoport A (1984) Theories of coalition formation. Erlbaum, Mahwah, NJ
Kenrick D, Li N, Butner J (2003) Dynamical evolutionary psychology: Individual decision rules and emergent social norms. Psychol Rev 110(1):3–28
Kluver J, Malecki R, Schmidt J, Stoica C (2003) Sociocultural evolution and cognitive ontogenesis: a sociocultural-cognitive algorithm. Comput Math Organ Theory 9:255–273
Kluver J, Schmidt J, Stoica C (2005) The emergence of social order by processes of typifying: a computational model. J Math Sociol 29:155–176
Lustick I (2000) Agent-based modeling of collective identity: testing constructivist theory. J Artif Soc Soc Simul 3(1) http://www.soc.surrey.ac.uk/JASSS/3/1/1.html
Mandler J (1992) How to build a baby. Psychol Rev 99(4):587–604
Moss S (1999) Relevance, realism and rigour: A third way for social and economic research. CPM Report No. 99-56. Center for Policy Analysis, Manchester Metropolitan University, Manchester, UK
Reber A (1989) Implicit learning and tacit knowledge. J Exp Psychol Gen 118(3):219–235
Reynolds R (1994) Learning to co-operate using cultural algorithms. In: Gilbert N, Doran J (eds) Simulating societies: the computer simulation of social phenomena. UCL Press, London, UK
Sawyer R (2003) Multiagent systems and the micro-macro link in sociological theory. Sociol Methods Res 31(3):325–363
Schacter D (1990) Toward a cognitive neuropsychology of awareness: Implicit knowledge and anosagnosia. J Clin Exp Neuropsychol 12(1):155–178
Seger C (1994) Implicit learning. Psychol Bull 115(2):163–196
Stadler M, Frensch P (1998) Handbook of implicit learning. Sage Publications, Thousand Oaks
Stanley W, Mathews R, Buss R, Kotler-Cope S (1989) Insight without awareness: on the interaction of verbalization, instruction and practice in a simulated process control task. Q J Exp Psychol 41A(3):553–577
Sun R (1995) Robust reasoning: Integrating rule-based and similarity-based reasoning. Artificial Intelligence 75(2):241–296
Sun R (2001) Cognitive science meets multi-agent systems: A prolegomenon. Philos Psychol 14(1):5–28
Sun R (2002) Duality of the mind. Lawrence Erlbaum Associates, Mahwah, NJ
Sun R (2003) A tutorial on CLARION 5.0. Technical report, Cognitive Science Department, Rensselaer Polytechnic Institute http://www.cogsci.rpi.edu/∼rsun/sun.tutorial.pdf
Sun R (ed) (2006) Cognition and multi-agent interaction: from cognitive modeling to social simulation. Cambridge University Press, New York
Sun R, Naveh I (2004) Simulating organizational decision-making using a cognitively realistic agent model. J Artif Soc Soc Simul 7(3) http://www.jasss.soc.surrey.ac.uk/7/3/5.html
Sun R, Peterson T (1998) Autonomous learning of sequential tasks: experiments and analyses. IEEE Trans Neural Netw 9(6):1217–1234
Sun R, Merrill E, Peterson T (2001) From implicit skills to explicit knowledge: a bottom-up model of skill learning. Cogn Sci 25(2):203–244
Sun R, Slusarz P, Terry C (2005) The interaction of the explicit and the implicit in skill learning: a dual-process approach. Psychol Rev 112(1):159–192
Tetlock P (2002) Social-functionalist frameworks for judgment and choice: the intuitive politician, theologian, and prosecutor. Psychol Rev 109:451–472
Tetlock P, Lebow RN (2001) Poking counterfactual holes in covering laws: cognitive styles and historical reasoning. Am Polit Sci Rev 95:829–843
Watkins C (1989) Learning with delayed rewards, PhD Thesis. Cambridge University, Cambridge, UK
Wynn T (2002) Archaeology and cognitive evolution. Brain Behav Sci 25(3):389–438
Zerubavel E (1997) Social mindscape: an invitation to cognitive sociology. Harvard University Press, Cambridge, MA
Acknowledgment
We acknowledge Xi Zhang for his assistance in conducting this simulation.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sun, R., Naveh, I. Social institution, cognition, and survival: a cognitive–social simulation. Mind & Society 6, 115–142 (2007). https://doi.org/10.1007/s11299-007-0027-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11299-007-0027-5