1) computer games
机器博弈
1.
Time Allocation is a typical and important strategy problem in chess matches,so does in computer games.
时间分配问题在象棋比赛中是十分重要的策略问题,在机器博弈中也是如此。
2) computer game
机器博弈
1.
Challenging issues facing computer game research;
机器博弈研究面临的各种挑战
2.
A model of computer game system is presented.
目的为机器博弈系统建立利于学习和研究的理论化模型。
3) machine adversarial
机器博弈
1.
Using adversarial search technologies with the evaluation function and then creating move generations in the game tree is the traditional methods,which is for solving the problems of machine adversarial.
解决机器博弈问题的传统方法是在博弈树上采用各种搜索算法,结合局面评估,来生成相应的走法。
4) machine game
机器博弈
1.
This article deals with PDC PROLOG based self learning machine game through problem solving on three in a diagonal.
通过“对角棋”问题的求解，研究基于ＰＤＣ－ＰＲＯＬＯＧ的机器博弈问题，提出了模型表达及自学习的程序实例。
2.
Presents a novel co-evolutionary genetic system(SANE),the algorithm use two populations to co-evolve feedback neural networks(FNN) which evaluate board positions in machine games.
阐述了一种典型的协同进化遗传算法(SANE),在机器博弈中,用前馈神经网络(FNN)表示局面估值函数,该算法采用两个种群合作协同的方式进化该FNN。
5) stochastic game
随机博弈
1.
The uncertain factors in electricity market that power generation companies will face with are analyzed, then a stochastic game model is built to realize bidding equilibrium of active power among these companies and a concept of virtual unit is led in to quantitatively calculate the energy shortage.
分析了市场环境下发电商面临的不确定性因素,建立了发电厂出力与报价均衡的随机博弈模型,引入了“虚拟机组”的概念对能源短缺进行定量计算。
2.
We propose a new cooperative reinforcement learning method based on the stochastic game in multi-agent systems.
本文针对一类追求系统得益最大化的协作团队的学习问题,基于随机博弈的思想,提出了一种新的多Agent协同强化学习方法。
6) game-playing
人机博弈
1.
As an example,Gobang game-playing program was studied.
以五子棋为例,用UML开发人机博弈程序。
补充资料：比较博弈法
比较博弈法是通过被调查者在不同的方案组合之间进行选择，调查被调查者的受偿意愿，最后确定环境质量的货币价值。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条