An important task in evolutionary biodemography is to determine the schedule of survival and reproduction as the outcome of natural selection acting on life histories. We do this by using a model in which the state of the organism is characterized by mass and accumulated damage, both of which are affected by activity and which affect the rate of mortality. Focusing on growth during the juvenile period, we determine the level of activity that maximizes reproductive value. Given this, we are able to project forward and determine the trajectory of mortality for an individual following the optimal life history, given the physiological and reproductive parameters. We show that there are two main classes of juvenile mortality trajectories: U-shaped (such as recently reported for prereproductive humans) and steadily declining and we are able to connect the shape of the mortality trajectory with the physiological and reproductive parameters characterizing the life history. Our work shows the importance of state in models of evolutionary biodemography and the power of modern computational methods to illuminate biological process.free-radical theory ͉ disposable soma ͉ life history theory ͉ dynamic programming D emography is, in part, the study of the implications of a schedule of survival and mortality. The goal is to describe patterns, understand pattern and process, and predict the consequences of change on those patterns. Evolutionary biodemography asks about the origins of such schedules, in the context of evolution of life histories by natural selection. Evolutionary biodemography seeks to merge demography with evolutionary thinking (2-6). The result, for example, will be to use the comparative method to explore similarities and differences of patterns across species and to understand the patterns and mechanisms of vital statistics as the result of evolution by natural (and sometimes artificial) selection. Raymond Pearl, one of the founders of quantitative population biology, understood the importance of doing this but lacked the mathematical tools to do so. For example, with John Miner (7) he wrote ''For it appears clear that there is no one universal 'law' of mortality. . . different species may differ in the age distribution of their dying just as characteristically as they differ in their morphology'' and that ''But what is wanted is a measure of the individual's total activities of all sorts, over its whole life; and also a numerical expression that will serve as a measure of net integrated effectiveness of all of the environmental forces that have acted upon the individual throughout its life''. With the development of state-dependent life history theory (8-10), the tools now exist.Here we respond to the challenge of Wachter (11), who noted that the evolutionary theories of aging generally fail to be able to predict the characteristics of mortality trajectories. To do this, we apply a recent development in state-dependent life history theory (12) that accounts for activity, the generation of cellular damage th...