Neural network approach for learning of the world structure by cognitive agents

Authors:
Agnieszka Pieczyńska;Jarosław Drapała
Affiliations:
Institute of Information Science and Engineering, Wrocław University of Technology, Wrocław, Poland;Institute of Information Science and Engineering, Wrocław University of Technology, Wrocław, Poland
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Year:
2006

Citing 5
Cited 0

The symbol grounding problem

CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Consensus system for solving conflicts in distributed systems

Information Sciences—Informatics and Computer Science: An International Journal
Construction of weak and strong similarity measures for ordered sets of documents using fuzzy set techniques

Information Processing and Management: an International Journal
An approach to resolving semantic inconsistency of multiple prepositional attitudes

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Identification and control of dynamical systems using the self-organizing map

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work an original method for coping with agents' incomplete knowledge is introduced. This method called the algorithm for the messages generation is applied by the cognitive agents when the states of external objects can not be directly perceived. To approximate the current states of objects all agent's experience as temporal data base is taken into account. As a result of the algorithm the logic formulas with modal operators are generated. One of the steps of proposed algorithm is the classification of the observations. It is shown how neural network approach might be used in order to determined some tendencies to occurrence specific states of objects.