This paper presents a problem-independent framework that uni es various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not ne...
The well-known backpropagation (BP) derivative computation process for multilayer perceptrons (MLP) learning can be viewed as a simplified version of the Kelley-Bryson gradient f...
Cooperative checkpointing uses global knowledge of the state and health of the machine to improve performance and reliability by dynamically deciding when to skip checkpoint reque...
Abstract. We present a general discussion of what constitutes a marketoriented approach to optimization. We demonstrate how a general framework can be used to conceptually improve ...
An evolutionary reinforcement-learning algorithm, the operation of which was not associated with an optimality condition, was instantiated in an artificial organism. The algorithm ...