PRM demographic evolution

HPRM: a hierarchical PRM

We introduce a hierarchical variant of the probabilistic roadmap method for motion planning. By recursively refining an initially sparse sampling in neighborhoods of the C-obstacle boundary, our algorithm generates a smaller roadmap that is more likely to find narrow passages than uniform sampling. We analyze the failure probability and computation time, relating them to path length, path clear...

Demographic and genetic constraints on evolution.

Populations unable to evolve to selectively favored states are constrained. Genetic constraints occur when additive genetic variance in selectively favored directions is absent (absolute constraints) or present but small (quantitative constraints). Quantitative--unlike absolute--constraints are presumed surmountable given time. This ignores that a population might become extinct before reaching...

Demographic Homeostasis and the Evolution of Senescence

Existing theories for the evolution of aging and death treat senescence as a side-effect of strong selection for fertility. These theories are well-developed mathematically, but fit poorly with emerging experimental data. The data suggest that aging is an adaptation, selected for its own sake. But aging contributes only negatively to fitness of the individual. What kind of population model woul...

Generalizing the Analysis of PRM

This paper presents a novel analysis of the probabilistic roadmap method (PRM) for path planning. We formulate the problem in terms of computing the transitive closure of a relation over a probability space and give a bound in terms of the number of intermediate points for some path and the probability of choosing a point from a certain set. Explicit geometric assumptions are not necessary to c...

Path Planning Using Lazy PRM