Title :
Dynamic Customization of Data Structures Instances Using an Agent Based Approach
Author :
Czibula, Istvan Gergely ; Czibula, Gabriela ; Guran, Adriana Mihaela
Author_Institution :
Dept. of Comput. Sci., Babes-Bolyai Univ., Cluj-Napoca, Romania
Abstract :
Abstract data types (ADTs) represent the core for any software application, and a proper use of them is an essential requirement for developing a robust and efficient system. Moreover, a proper instantiation of a data structure that implements an abstract data type can greatly impact the performance of the system. In this paper we propose a learning approach for the dynamic configuration of data structures instances in a software system. In order to adapt a data structure to the system´s current execution context, a neural network will be used and an agent based system is proposed. We experimentally evaluate our system on a case study, emphasizing the advantages of the proposed approach.
Keywords :
abstract data types; learning (artificial intelligence); neural nets; software agents; abstract data types; agent based approach; data structures instances; dynamic customization; neural network; software application; Application software; Computer science; Data structures; Machine learning; Neural networks; Robustness; Scientific computing; Software algorithms; Software systems; Supervised learning; agent-based system; data structure; machine learning;
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2009 11th International Symposium on
Conference_Location :
Timisoara
Print_ISBN :
978-1-4244-5910-0
Electronic_ISBN :
978-1-4244-5911-7
DOI :
10.1109/SYNASC.2009.25
