We introduce an analytical model that predicts the dynamics of a simple evolutionary algorithm in terms of the flow in the space of fitness distributions. In the limit of infinite populations the equations of motion are derived in closed form. We show how finite populations induce periods of...

We analyze the population dynamics of a broad class of fitness functions that exhibit epochal evolution|a dynamical behavior, commonly observed in both natural and artificial evolutionary processes, in which long periods of stasis in an evolving population are punctuated by sudden bursts of...

Technological change at the firm level has commonly been modeled as random sampling from a fixed distribution o f possibilities. Such models, however, typically ignore empirically important aspects of the firm's search process, notably the observation that the present state of the firm guides...

Epochal dynamics, in which long periods of stasis in population fitness are punctuated by sudden innovations, is a common behavior in both natural and artificial evolutionary processes. We use a recent quantitative mathematical analysis of epochal evolution to estimate, as a function of...

During an immune response the affinity of antibodies that react with the antigen that triggered the response increases with time, a phenomenon known as affinity maturation. The molecular basis of affinity maturation has been partially elucidated. It involves the somatic mutation of immunoglobin...

We compare the frequency distribution of gene family sizes in the complete genomes of five Bacteria ({\it Escherichia coli, Haemophilus influenzae, Mycoplasma genitalium, Mycoplasma pneumoniae,} and {\it Synechocystis sp. PCC6803}), one Archaeon ({\it Methanococcus janaschii}), one eukaryote...

Dynamics is not enough for cognition nor is it a substitute for information processing aspects of brain behavior. Moreover, dynamics and computation are not at odds, but are quite compatible. They can be synthesized so that any dynamical system can be analyzed in terms of its intrinsic...

Computational mechanics, an approach to structural complexity, defines a process's causal states and gives a procedure for finding them. We show that the causal-state representation--an e-machine--is the minimal one consistent with accurate prediction. We establish several results on e-machine...

We introduce a class of embedded-particle models for describing the emergent computational strategies observed in cellular automata (CAs) that were evolved for performing certain computational tasks. The models are evaluated by comparing their estimated performances with the actual performances...