C4.5: programs for machine learning
C4.5: programs for machine learning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Strategy-Based learning through communication with humans
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
A comparison between a communication-based and a data mining-based learning approach for agents
Intelligent Decision Technologies
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Programming of software agents is a difficult task. As a result, online learning techniques have been used in order to make software agents automatically learn to decide proper condition-action rules from their experiences. However, for complicated problems this approach requires a large amount of time and might not guarantee the optimality of rules. In this paper, we discuss our study to apply decision-making behaviors of humans to software agents, when both of them are present in the same environment. We aim at implementation of human instincts or sophisticated actions that can not be easily achieved by conventional multiagent learning techniques. We use RoboCup simulation as an experimenting environment and validate the effectiveness of our approach under this environment.