Abstract. This paper investigates symbolic heuristic search with BDDs for solving domain-independent action planning problems cost-optimally. By distributimpact of operators that t...
—This paper describes the application of various search techniques to the problem of automatic empirical code optimization. The search process is a critical aspect of auto-tuning...
Abstract. Heuristic programming was the first area in which AI methods were tested. The favourite case-studies were fairly simple toyproblems, such as cryptarithmetic, games, such ...
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 success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...