Neural network-based ideation learning for intelligent agents: e-brainstorming with privacy preferences
by S. Manju; M. Punithavalli
International Journal of Computational Vision and Robotics (IJCVR), Vol. 5, No. 3, 2015

Abstract: Creative thinking provide ways to many technical ideas, were new innovations will come to existence. For a single problem there can be numerous innovative solutions, it is very important to make evaluation and selection of ideas to achieve better results. E-brainstorming is an electronic version of sharing ideas. This paper integrates associative thinking of humans with an intelligent agent method to develop a neural network-based learning agent that can be represented as e-brainstorming session participant. Computer aided brainstorming decision model (CABDM) is built to construct an environment where neural network-based agents can learn rules from the database and make decisions. Additionally, privacy preferences, flexible ideation map construction are adopted to enhance e-brainstorming technique. The preliminary evaluation results indicates that the proposed work advances the existing agent-based e-Brainstorming by introducing neural network-based agents, with flexible ideation map to reduce production blocking problem by improving the productivity of e-brainstorming session.

Online publication date: Fri, 21-Aug-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Vision and Robotics (IJCVR):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com