Neural networks for pattern recognition
Neural networks for pattern recognition
A genetic agent-based negotiation system
Computer Networks: The International Journal of Computer and Telecommunications Networking
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
On the Morality of Artificial Agents
Minds and Machines
Multi-agent Negotiation Model Based on RBF Neural Network Learning Mechanism
IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
An artificial neural network approach for creating an ethical artificial agent
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Classification of seismic signals by integrating ensembles ofneural networks
IEEE Transactions on Signal Processing
Evolutionary ensembles with negative correlation learning
IEEE Transactions on Evolutionary Computation
Generating useful test data for complex linked employer-employee datasets
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
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Negotiation is one of the most prevalent methods that agents, in a multi-agent system, use to reach agreements. Nowadays, one important aspect of negotiation is moral behaviors of agents that involve in negotiation. For this reason, we propose an ethical classifier that uses artificial neural networks ensembles. To evaluate the performance of the proposed method, we conduct experiments including comparisons with alternative methods for ethical classification. As the result of experiments suggest, the proposed method shows improved ethical recognition performance, in comparison with other widely used methods.