Complexity and Context-Dependency
- Bruce Edmonds
- … show all 1 hide
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.Get Access
It is argued that given the “anti-anthropomorphic” principle—that the universe is not structured for our benefit—modelling trade-offs will necessarily mean that many of our models will be context-specific. It is argued that context-specificity is not the same as relativism. The “context heuristic”—that of dividing processing into rich, fuzzy context-recognition and crisp, conscious reasoning and learning—is outlined. The consequences of accepting the impact of this human heuristic in the light of the necessity of accepting context-specificity in our modelling of complex systems is examined. In particular the development of “islands” or related model clusters rather than over-arching laws and theories. It is suggested that by accepting and dealing with context (rather than ignoring it) we can push the boundaries of science a little further.
- Axtell R. L., Epstein J. M. (1994) Agent-based modelling: Understanding our creations. The Bulletin of the Santa Fe Institute 9: 28–32
- Cartwright N. (1983) How the laws of physics lie. Clarendon Pres, Oxford CrossRef
- Edmonds, B. (1999a). The pragmatic roots of context. CONTEXT’99, Trento, Italy, September 1999. Lecture notes in artificial intelligence (Vol. 1688, pp. 119–132).
- Edmonds, B. (1999b). Syntactic measures of complexity. PhD Thesis, University of Manchester, Manchester. http://bruce.edmonds.name/thesis/.
- Edmonds, B. (2001). The use of models—making MABS actually work. In: S. Moss, & P. Davidsson (Eds.), Multi agent based simulation, Lecture notes in artificial intelligence (Vol. 1979, pp. 15–32).
- Edmonds, B. (2002). Learning and exploiting context in agents. In Proceedings of the 1st international joint conference on autonomous agents and multiagent systems (AAMAS) (pp. 1231–1238). Bologna: ACM Press.
- Edmonds, B. (2007a). Simplicity is not truth-indicative. In C. C. Gershenson, D. Aerts, & B. Edmonds (Eds.), Philosophy and complexity (pp. 65–80). Singapore: World Scientific.
- Edmonds B. (2007b) The practical modelling of context-dependent causal processes. Chemistry and Biodiversity 4(1): 2386–2395 CrossRef
- Edmonds, B. (2009). The nature of noise. In F. Squazzoni (Ed.) Epistemological aspects of computer simulation in the social sciences. Lecture notes in artificial intelligence (Vol. 5466, pp. 169–182).
- Edmonds B., Hales D. (2005) Computational simulation as theoretical experiment. Journal of Mathematical Sociology 29(3): 209–232 CrossRef
- Edmonds, B., & Norling, E. (2007). Integrating learning and inference in multi-agent systems using cognitive context. In L. Antunes & K. Takadama (Eds.), Multi-agent-based simulation VII. Lecture notes in artificial intelligence (Vol. 4442, pp. 142–155).
- Giere R. N. (1988) Explaining science: A cognitive approach Chicago. University of Chicago Press, London CrossRef
- Greiner R., Darken C., Santoso N. I. (2001) Efficient reasoning. ACM Computing Surveys 33(1): 1–30 CrossRef
- Gunsteren W. F., Berendsen H. J. C. (1990) Computational simulation of molecular dynamics: Methodology, applications and perspectives in chemistry. Angewandte Chemie International Edition in English 29: 992–1023 CrossRef
- Hayes, P. (1995). Contexts in context. Context in knowledge representation and natural language, AAAI fall symposium, November 1997, Cambridge: MIT.
- Kokinov, B., & Grinberg, M. (2001). Simulating context effects in problem solving with AMBR. In V. Akman, P. Bouquet, R., Thomason, & R. A. Young (Eds.), Modelling and using context (Vol. 2116, pp. 221–234). Springer, Berlin.
- McCarthy J. (1971) Generality in artificial-intelligence—turing award lecture. Communications of the ACM 30(12): 1030–1035 CrossRef
- McCarthy J., Hayes P. J. (1969) Some philosophical problems from the standpoint of artificial intelligence. Machine Intelligence 4: 463–502
- Pearl J. (2000) Causality. Cambridge University Press, Cambridge
- Schlosser, A., Voss, M., & Brückner, L. (2005). On the simulation of global reputation systems. Journal of Artificial Societies and Social Simulation 9(1):4 http://jasss.soc.surrey.ac.uk/9/1/4.html.
- Tykhonov, D., Jonker, C., Meijer, S., & Verwaart, T. (2008). Agent-based simulation of the trust and tracing game for supply chains and networks. Journal of Artificial Societies and Social Simulation 11(3):1 http://jasss.soc.surrey.ac.uk/11/3/1.html.
- Wheeler M., Clark A. (1999) Genic representation: Reconciling content and causal complexity. British Journal for the Philosophy of Science 50(1): 103–135 CrossRef
- Zadrozny, W. (1997). A pragmatic approach to context. Context in knowledge representation and natural language, AAAI fall symposium, November 1997 Cambridge: MIT.
- Complexity and Context-Dependency
Foundations of Science
Volume 18, Issue 4 , pp 745-755
- Cover Date
- Print ISSN
- Online ISSN
- Springer Netherlands
- Additional Links
- Bruce Edmonds (1)
- Author Affiliations
- 1. Centre for Policy Modelling, Manchester Metropolitan University, Manchester, UK