the generative sciences

The generative sciences (or generative science) are the interdisciplinary and multidisciplinary sciences that explore the natural world and its complex behaviours as a generative process. Generative science shows how deterministic and finite rules and parameters in the natural phenomena interact with each other to generate indeterministic and infinite behaviour. These sciences include psychology and cognitive science, cellular automata, generative linguistics, natural language processing, social network analysis, connectionism, evolutionary biology, self-organization, neural network theory, communication networks, neuromusicology, information theory, systems theory, genetic algorithms, artificial life, chaos theory, complexity theory, epistemology, systems thinking, genetics, philosophy of science, cybernetics, bioinformatics, and catastrophe theory.



Generating multilevel dynamical processes in Physics and Psychology
http://www.generativescience.org/

an article:
Quantum Mechanics and Consciousness:
A Causal Correspondence Theory
Ian J. Thompson
Physics Department, University of Surrey, Guildford GU2 5XH, U.K
October, 1990.
We may suspect that quantum mechanics and consciousness are related, but the details are not at all clear. In this paper, I suggest how the mind and brain might fit together intimately while still maintaining distinct identities. The connection is based on the correspondence of similar functions in both the mind and the quantum-mechanical brain.

other article:
Generative Social Science:
Studies in Agent-Based Computational Modeling
Joshua M. Epstein
Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation.