Dehu Qi

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This paper presents a new genetic K-means approach. Instead of evolving the centroid population, this new approach evolves the weights associated with the keywords, which character each class. The approach is implemented as a hierarchical automated Web page classifier for automated Web page classification. Initial experimental results are very promising and(More)
This paper presents a multi-agent reinforcement learning bidding approach (MARLBS) for performing multi-agent reinforcement learning. MARLBS integrates reinforcement learning, bidding and genetic algorithms. The general idea of our multi-agent systems is as follows: There are a number of individual agents in a team, each agent of the team has two modules: Q(More)
A cooperative team of agents may perform many tasks better than single agents. The question is how cooperation among self-interested agents should be achieved. It is important that, while we encourage cooperation among agents in a team, we maintain autonomy of individual agents as much as possible, so as to maintain flexibility and generality. This paper(More)
A cooperative team of agents may perform many tasks better than isolated agents. The question is how cooperation among self-interested agents may be achieved. It is important that, while we encourage cooperation among agents to form a team, we maintain autonomy of individual agents as much as possible, so as to maintain flexibility and generality. This(More)
A cooperative team of agents may perform many tasks better than single agents. The question is how cooperation among self-interested agents should be achieved. It is important that, while we encourage cooperation among agents in a team, we maintain autonomy of individual agents as much as possible, so as to maintain flexibility and generality. This paper(More)
One of the main research topics in multiagent systems is learning cooperation among agents. This paper presents a multiagent reinforcement learning approach with bidding. Self-interested agents cooperate with each other through bidding and evolutionary computation. We tested the approach to the TSP problem. The experimental results show our approach can(More)