Contextual Stochastic Search

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Abdolmaleki, A (Author) Other; lau, n (Author) FCUP; reis, lp (Author) REIT; Neumann, G (Author) Other

Conference proceedings International

Title: PROCEEDINGS OF THE 2016 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'16 COMPANION)

Pages: 29-30

Genetic and Evolutionary Computation Conference (GECCO)

Denver, CO, JUL 20-24, 2016

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 3 Citations

Other information

Authenticus ID: P-00K-Q6K

DOI: 10.1145/2908961.2909012

Abstract (EN): Many stochastic search algorithms require relearning if the task changes slightly to adapt the solution to the new situation or the new context. Therefore in this research, we investigate the contextual stochastic search algorithms that can learn from multiple tasks simultaneously. Here, we want to find good parameter vectors for multiple related tasks, where each task is described by a continuous context vector. Hence, the objective function might change slightly for each parameter vector evaluation.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 2