Biomedical subjects

JM Carlson

Publications and source records attributed to JM Carlson.

16 recordsLinked to original sources

PubMed2000

Power laws, highly optimized tolerance, and generalized source coding

We introduce a family of robust design problems for complex systems in uncertain environments which are based on tradeoffs between resource allocations and losses. Optimized solutions yield the "robust, yet fragile" features of highly optimized tolerance and exhibit power law tails in the distributions of events for all but the special case of Shannon coding for data compression. In addition to data compression, we construct specific solutions for world wide web traffic and forest fires, and obtain excellent agreement with measured data.

Journal Article↗

PubMed2000

Highly optimized tolerance: robustness and design in complex systems

Highly optimized tolerance (HOT) is a mechanism that relates evolving structure to power laws in interconnected systems. HOT systems arise where design and evolution create complex systems sharing common features, including (1) high efficiency, performance, and robustness to designed-for uncertainties, (2) hypersensitivity to design flaws and unanticipated perturbations, (3) nongeneric, specialized, structured configurations, and (4) power laws. We study the impact of incorporating increasing levels of design and find that even small amounts of design lead to HOT states in percolation.

Journal Article↗

PubMed2000

Dynamics and changing environments in highly optimized tolerance

Highly optimized tolerance (HOT) is a mechanism for power laws in complex systems based on the robust design of systems in uncertain environments. Once the system, the environment, and the optimization scheme have been specified, the HOT state is fixed and corresponds to the set of measure zero (typically a single point) in the configuration space which minimizes a cost function U. Here we explore the U-dependent structures in configuration space which are associated with departures from the optimal state. We introduce dynamics, quantified by an effective temperature T, such that T=0 corresponds to the original HOT state, while T-->infinity corresponds to completely random configurations. More generally, T defines the range in state space over which fluctuations are likely to be observed. In a fixed environment fluctuations always raise the average cost. However, in a time-dependent environment, mobile configurations can lower the average U because they adjust more efficiently to changes.

Journal Article↗

PubMed1996