A novel method was designed to solve reinforcement learning problems with artificial potential field.Firstly a reinforcement learning problem was transferred to a path planning problem by using artificial potential fi...A novel method was designed to solve reinforcement learning problems with artificial potential field.Firstly a reinforcement learning problem was transferred to a path planning problem by using artificial potential field(APF),which was a very appropriate method to model a reinforcement learning problem.Secondly,a new APF algorithm was proposed to overcome the local minimum problem in the potential field methods with a virtual water-flow concept.The performance of this new method was tested by a gridworld problem named as key and door maze.The experimental results show that within 45 trials,good and deterministic policies are found in almost all simulations.In comparison with WIERING's HQ-learning system which needs 20 000 trials for stable solution,the proposed new method can obtain optimal and stable policy far more quickly than HQ-learning.Therefore,the new method is simple and effective to give an optimal solution to the reinforcement learning problem.展开更多
中国科学院过程工程所(原化工冶金所)自1997年开始建立和维护的Internet化学化工资源导航系统ChIN,目前作为国家科学数字图书馆:化学学科信息门户运行,它是一个集Internet化学资源的发现、收集、分类、描述,门户网站导航系统的生成和向...中国科学院过程工程所(原化工冶金所)自1997年开始建立和维护的Internet化学化工资源导航系统ChIN,目前作为国家科学数字图书馆:化学学科信息门户运行,它是一个集Internet化学资源的发现、收集、分类、描述,门户网站导航系统的生成和向Web发布、用户集成交流环境等功能较为完善的化学化工门户系统。ChIN已经在Internet上连续不间断地运行了约10年时间。目前与国际上知名的同类系统如ChemDex、Links for Chemists等相比,无论从索引的资源总量、内容质量、还是系统的整体性能上。ChIN都毫不逊色。本文回顾了ChIN在这10年中工具与版本的发展、运行的概况、及被访问的情况等。展开更多
基金Projects(30270496,60075019,60575012)supported by the National Natural Science Foundation of China
文摘A novel method was designed to solve reinforcement learning problems with artificial potential field.Firstly a reinforcement learning problem was transferred to a path planning problem by using artificial potential field(APF),which was a very appropriate method to model a reinforcement learning problem.Secondly,a new APF algorithm was proposed to overcome the local minimum problem in the potential field methods with a virtual water-flow concept.The performance of this new method was tested by a gridworld problem named as key and door maze.The experimental results show that within 45 trials,good and deterministic policies are found in almost all simulations.In comparison with WIERING's HQ-learning system which needs 20 000 trials for stable solution,the proposed new method can obtain optimal and stable policy far more quickly than HQ-learning.Therefore,the new method is simple and effective to give an optimal solution to the reinforcement learning problem.
文摘中国科学院过程工程所(原化工冶金所)自1997年开始建立和维护的Internet化学化工资源导航系统ChIN,目前作为国家科学数字图书馆:化学学科信息门户运行,它是一个集Internet化学资源的发现、收集、分类、描述,门户网站导航系统的生成和向Web发布、用户集成交流环境等功能较为完善的化学化工门户系统。ChIN已经在Internet上连续不间断地运行了约10年时间。目前与国际上知名的同类系统如ChemDex、Links for Chemists等相比,无论从索引的资源总量、内容质量、还是系统的整体性能上。ChIN都毫不逊色。本文回顾了ChIN在这10年中工具与版本的发展、运行的概况、及被访问的情况等。
