[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f2wYMs8jPT5h8pTHgV_qTgLLBb2GV0wgmxP_Rw26IJpE":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":30,"type":31},[],"2024-01-02 16:06:05",125610330,[8,9,10,11],"蚂蚁系统是一种增强型学习系统","蚁群算法中,蚂蚁选择路径的原理是一种负反馈机制","蚁群算法是一种应用于组合优化问题的启发式搜索算法","蚁群算法是通过人工模拟蚂蚁搜索食物的过程,即通过个体之间的信息交流与相互协作最终找到从蚁穴到食物源的最短路径的",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},10,"c79cad0bb845eb2079bd2ef77a8d97ad","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F25b30343053994e8940089572d36015b.jpg","人工智能导论","work_31864337","作业4:智能计算","关于蚁群算法,下面叙述正确的是( )",[21,32,41,50,58,63,68,73,78,81],{"answer":22,"createTime":5,"id":23,"options":24,"question":29,"source":30,"type":31},[],125610301,[25,26,27,28],"交叉","杂交","选择","变异","基本遗传算法的基本遗传算子不包括( )算子","v1",1,{"answer":33,"createTime":5,"id":34,"options":35,"question":40,"source":30,"type":31},[],125610303,[36,37,38,39],"粒子群优化算法中的个体除了有位置和速度外,还有着过去的历史信息(pBest、gBest)","粒子群优化算法强调"协同合作",不好的个体通过学习向好的方向转变","粒子群优化算法与遗传算法都属于全局优化方法","粒子群优化算法中最好的个体通过产生更多的后代来传播基因","下面说法错误的是( )",{"answer":42,"createTime":5,"id":43,"options":44,"question":49,"source":30,"type":31},[],125610305,[45,46,47,48],"粒子群优化算法","蚁群优化算法","A星搜索算法","布谷鸟优化算法","下面不属于群体智能优化算法的是( )",{"answer":51,"createTime":5,"id":52,"options":53,"question":56,"source":30,"type":57},[],125610308,[54,55],"正确","错误","遗传算法的适应度函数是用来区分群体中的个体好坏的标准",3,{"answer":59,"createTime":5,"id":60,"options":61,"question":62,"source":30,"type":57},[],125610314,[54,55],"遗传算法中起核心作用的是变异算子",{"answer":64,"createTime":5,"id":65,"options":66,"question":67,"source":30,"type":57},[],125610317,[54,55],"‌在遗传算法应用中,适应度函数的设计要结合问题本身的要求而定,但适应度函数和问题的目标函数没有关系",{"answer":69,"createTime":5,"id":70,"options":71,"question":72,"source":30,"type":57},[],125610321,[54,55],"粒子群优化算法中,个体认知分量表示粒子本身的思考,它是在对粒子现有的位置和群体经历过的最优位置进行比较后得到的",{"answer":74,"createTime":5,"id":75,"options":76,"question":77,"source":30,"type":57},[],125610326,[54,55],"蚂蚁在运动过程中,根据各条路径上的信息素决定转移方向",{"answer":79,"createTime":5,"id":6,"options":80,"question":19,"source":30,"type":31},[],[8,9,10,11],{"answer":82,"createTime":83,"id":84,"options":85,"question":86,"source":30,"type":87},[],"2024-01-11 15:21:29",130450942,[],"利用基本遗传算法求解旅行商问题,假设有8个城市,分别是12345678.由于交叉,可能会出现不满足约束条件的非法染色体,请使用部分匹配交叉策略解决非法染色的问题.如下所示,A和B表示父串,竖线表示交叉点, A = 1 3 4 | 8 2 7 |5 6 B = 8 6 3 | 1 2 5 |7 4 那么交叉后的子串A'' = 83412576,B'' = ( ),填写时注意数字之间不要有空格、竖线等其他字符",2]