In stochastic (dynamic) traffic assignment (DTA), route choice (RC) formulations with implicit set require less memory than their explicit counterparts. To compute turn probabilities, however, a topological ordering of the nodes is needed, which negatively impacts stability convergence and consistency equilibrium. This paper formulates general framework for RC module efficient DTA (ESDTA) witho...

Martingale theory yields a powerful set of tools that have recently been used to prove quantitative properties of stochastic systems such as stochastic safety and qualitative properties such as almost sure termination. In this paper, we examine proof techniques for establishing almost sure persistence and recurrence properties of infinite-state discrete time stochastic systems. A persistence pr...

The Multi-Handler Knapsack Problem under Uncertainty (MHKPu) is a new stochastic knapsack problem where, given a set of items, characterized by volume and random profit, and a set of potential handlers, we want to find a subset of items which maximizes the expected total profit. The item profit is given by the sum of a deterministic profit plus a stochastic profit due to the random handling cos...

We train two convolutional neural networks on the POFA and NimStim datasets to identify individuals and identify emotions, respectively. In order to train these neural networks, we use two separate optimization procedures, the minFunc package and stochastic gradient descent. The minFunc optimization package achieved a 95.8% on the training set and achieved a 90.0% accuracy on the partitioned te...