We present a new algorithm for conformant probabilistic planning, which for a given horizon produces a plan that maximizes the probability of success under quantified uncertainty ...
Computational science is placing new demands on optimization algorithms as the size of data sets and the computational complexity of scientific models continue to increase. As thes...
Travis J. Desell, David P. Anderson, Malik Magdon-...
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell i...
This study proposes an agent-based model where adaptively learning agents with local vision who are situated in the Prisoner’s Dilemma game change their strategy and location as...