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Dynamics of Complex Interconnected Biological Systems Softcover Repri Edition
Contributor(s): Jennings (Author), Mees (Author), Vincent (Author)
ISBN: 1468467867     ISBN-13: 9781468467864
Publisher: Birkhauser
OUR PRICE:   $52.24  
Product Type: Paperback
Published: March 2012
Qty:
Additional Information
BISAC Categories:
- Mathematics | Applied
- Computers | Computer Simulation
Dewey: 003.3
Series: Mathematical Modeling
Physical Information: 0.72" H x 6.14" W x 9.21" (1.07 lbs) 334 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
This volume contains the proceedings of the U.S. Australia workshop on Complex Interconnected Biological Systems held in Albany, Western Australia January 1-5, 1989. The workshop was jointly sponsored by the Department of Industry, Trade and Commerce (Australia), and the Na- tional Science Foundation (USA) under the US-Australia agreement. Biological systems are typically hard to study mathematically. This is particularly so in the case of systems with strong interconnections, such as ecosystems or networks of neurons. In the past few years there have been substantial improvements in the mathematical tools available for study- ing complexity. Theoretical advances include substantially improved un- derstanding of the features of nonlinear systems that lead to important behaviour patterns such as chaos. Practical advances include improved modelling techniques, and deeper understanding of complexity indicators such as fractal dimension. Game theory is now playing an increasingly important role in under- standing and describing evolutionary processes in interconnected systems. The strategies of individuals which affect each other's fitness may be incor- porated into models as parameters. Strategies which have the property of evolutionary stabilty result from particular parameter values which may be the main feature of living determined using game theoretic methods. Since systems is that they evolve, it seems appropriate that any model used to describe such systems should have this feature as well. Evolutionary game theory should lead the way in the development of such methods.