We propose a multi-strategy method of learning domain-specific hyponymous relations.
我们提出了一种学习特定领域下位关系的多策略方法。
Based on soccer robot simulation as its research platform, this paper studies the learning of high level strategy of multi-agent adversarial system.
本文以足球仿真机器人系统为研究平台，研究多智能体对抗系统的高层策略学习问题。
In this paper, a new method which combines unsupervised and supervised learning strategy is put forward to construct the multi classification decision tree.
提出了一种融合无监督和监督两种学习策略生成多分类决策树的方法。
Comparative exrepriemts show that the proposed approach can give satisfactory results(2) Proposing a multi-strategy method of learning domain-specific hyponymous relations.
通过与分词系统实验结果相比，验证了该方法的有效性。 （2）多策略的领域概念上下位关系学习方法。
The paper proposes improved automated negotiation model and integrated negotiation strategy based on multi-strategy, designs learning mechanism based on reinforcement learning.
提出改进的自动谈判模型、基于多种策略的综合谈判策略，设计基于强化学习的学习机制。
The paper proposes improved automated negotiation model and integrated negotiation strategy based on multi-strategy, designs learning mechanism based on reinforcement learning.
提出改进的自动谈判模型、基于多种策略的综合谈判策略，设计基于强化学习的学习机制。
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