• Corpus ID: 18422470

AN INTRODUCTION TO CULTURAL ALGORITHMS

@inproceedings{Reynolds2008ANIT,
  title={AN INTRODUCTION TO CULTURAL ALGORITHMS},
  author={Robert G. Reynolds},
  year={2008}
}
In this paper a computational model of the cultural evolution process is described. This model integrates several traditional approaches to modeling cultural evolution into a common conceptual framework. This framework depicts cultural evolution as a process of dual inheritance. At the micro-evolutionary level there is a population of individuals, each described in terms of a set of behavioral traits. Traits are passed from generation to generation at this level by means of a number of socially… 
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References

SHOWING 1-7 OF 7 REFERENCES
An introduction to simulated evolutionary optimization
  • D. Fogel
  • Computer Science
    IEEE Trans. Neural Networks
  • 1994
TLDR
The development of each of these procedures over the past 35 years is described and some recent efforts in these areas are reviewed.
Version spaces: an approach to concept learning.
TLDR
The version space approach has been implemented as one component of the Meta-DENDRAL program for learning production rules in the domain of chemical spectroscopy and proofs are given for the correctness of the method for representing version spaces, and of the associated concept learning algorithm, for any countably infinite concept description language.
Adaptation in natural and artificial systems
TLDR
Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Dynamic Modeling in Archaeology: What, When, and Where?
  • Dynamical Modeling and the Study of Change in Archaeology, S. E. van der Leeuw
  • 1994
Renfrew, "Dynamic Modeling in Archaeology: What, When, and Where?
  • Dynamical Modeling and the Study of Change in Archaeology,
  • 1994
Parallel Bidirectional Heuristic Searching
  • Proceedings of Canadian Information Processing Society
  • 1987