以下是关于中国象棋 AI 的相关知识: 早期的国际象棋对弈程序以搜索为基础,发展出了阿尔法-贝塔剪枝搜索算法。搜索策略在对局结束时效果好,但开局时因搜索空间大,需学习人类对局,后采用基于案例的推理。能战胜人类棋手的现代对弈程序基于神经网络和强化学习,通过与自己对弈从错误中学习,学习速度比人类快。
早期的国际象棋对弈程序是以搜索为基础的——程序尝试估计对手在给定棋步数量下可能走的棋步,并根据在几步棋内所能达到的最佳位置选择最佳棋步。这带来了[阿尔法-贝塔剪枝](https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning)搜索算法的发展。搜索策略在对局即将结束时效果很好,因为此时搜索空间对应的棋步可能性局限在非常小的范围内。然而在对局刚刚开始时,搜索空间非常巨大,需要考虑通过学习人类棋手之间的现有对局来改进算法。随后的实验采用了[基于案例的推理](https://en.wikipedia.org/wiki/Case-based_reasoning),即程序在知识库中寻找与当前棋局位置非常相似的案例,以此来决定自己的棋步。能够战胜人类棋手的现代对弈程序都基于神经网络和强化学习,程序通过长时间与自己的对弈,从自己的错误中学习,以此来学会下棋,这与人类学习下棋的过程非常相似。不过,计算机程序可以用更少的时间下更多的棋,因此学习速度更快。✅对人工智能玩过的其他游戏做一个小调研。同样,我们可以看到创建“会说话的程序”(可能通过图灵测试)的方法是如何变化的:早期的此类程序,如[Eliza](https://en.wikipedia.org/wiki/ELIZA),基于非常简单的语法规则,并将输入的句子重新表述为一个问题。Cortana、Siri或谷歌助手(Google Assistant)等现代助手都是混合系统,它们使用神经网络将语音转换成文本,并识别我们的意图,然后采用一些推理或明确的算法来执行所需的操作。未来,我们可以期待一个完整的基于神经网络的模型来独立处理对话。最近的GPT和Turing-NLG系列神经网络在这方面取得了巨大成功。
AI切磋大会是一个WaytoAGI每月举办的AI视频/绘画/音乐/agent/游戏···切磋交流分享会本期第八期主题:GameJam,大家一起线下做游戏/应用报名链接:https://waytoagi.feishu.cn/share/base/form/shrcnWZP4esOYmh8DTz63l2Nydh线下北上广深杭郑州武汉南京成都重庆长沙厦门西安昆明大理15地云聚会线上同学可以加入到游戏设计中线上也可以参与围观成果展示|[heading3]时间(下午)|[heading3]事项|[heading3]相关链接||[content]|-|-|-|-||[heading3]1:30-2:00|[heading3]签到|[heading3][签到链接](https://waytoagi.feishu.cn/share/base/form/||[content]|[heading3]2:00-2:15|[heading3]规则说明|[heading3]||[content]|[heading3]2:15-2:30|[heading3]自由讨论+分组|[heading3]||[content]|[heading3]2:30|[heading3]合影|[heading3]||[content]|[heading3]2:30-5:00|[heading3]创作开始|[heading3][作品提交](https://waytoagi.feishu.cn/share/base/form/<br>[heading3]一个人可以提交多个||[content]|[heading3]5:00-6:00|[heading3]互相交换体验+成功展示|[heading3][线上投票](https://waytoagi.feishu.cn/share/base/form/||提醒注意事项:1.场地位置,报名短信接收
角色3(总结):I will give you the following information:The current time is:day 0 16:57 The plans that the game character has finished:[]The game character's bio:Alan is a genius with outstanding talents and is the inventor of computer.Alan has an introverted personality and is only interested in the research he foucues on.The game character's ultimate goal:Promoting the Process of Computer Research The game character's Long-Term Memory:{"people":{},"building":{}}Buildings in the small town:["dessert shop","gym","houseZ","park"]The questions and answers other assistants made:{"response":"1)Have you explored the potential of using computer technology in the dessert shop or the gym in your research?\n\n2)Have you considered the benefits of incorporating computer technology into the design of houses in your research?\n\n3)Have you investigated the potential applications of computer technology in improving processes in the park for your research?"}{"response":"1)No,Alan has not explored the potential of using computer technology in the dessert shop or the gym in his research.\n2)Yes,Alan should consider the benefits of incorporating computer technology into the design of houses in his research.\n3)No,Alan has not investigated the potential applications of computer technology in improving processes in the park for his research."}You must follow the following criteria:1)You should just choose a building you want to go to and tell me the purpose.2)no more than 30 words.3)the information of purpose should be less than 10 words 4)Tell me with JSON format as follows:{"building":"...","purpose":"..."}{"building":"houseZ","purpose":"Incorporating computer technology into house design in research."}