Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2009
Abstract
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic representation in developing agents. Some novel techniques are introduced that enables the neural network to process and manipulate sequential and hierarchical structures of information. It is suggested that by incorporating intentional agent model which relies on explicit symbolic description with self-organizing neural networks that are good at learning and recognizing patterns, the best from both sides can be exploited. This paper demonstrates that plans can be represented as weighted connections and reasoning processes can be accommodated through multidirectional activations accross different modalities of patterns. The network seamlessly interleaves planning and learning processes towards achieving the goal. Case studies and experiments shows that the model can be used to execute, plan, and capture plans as recipes through experiences.
Keywords
BDI agent, Fusion ART, IFALCON
Discipline
Artificial Intelligence and Robotics | Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Proceedings of 8th International Joint Conference on Autonomous Agents and Multiagent Systems 2009, AAMAS 2009, Budapest, Hungary, May 10-15
Volume
2
First Page
982
Last Page
989
ISBN
9781615673346
Identifier
10.5555/1558109.1558164
Publisher
International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
City or Country
Budapest
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.