Multi-agent reinforcement learning has recently been applied to solve pursuit problems.However,it suffers from a large number of time steps per training episode,thus always struggling to converge effectively,resulting...Multi-agent reinforcement learning has recently been applied to solve pursuit problems.However,it suffers from a large number of time steps per training episode,thus always struggling to converge effectively,resulting in low rewards and an inability for agents to learn strategies.This paper proposes a deep reinforcement learning(DRL)training method that employs an ensemble segmented multi-reward function design approach to address the convergence problem mentioned before.The ensemble reward function combines the advantages of two reward functions,which enhances the training effect of agents in long episode.Then,we eliminate the non-monotonic behavior in reward function introduced by the trigonometric functions in the traditional 2D polar coordinates observation representation.Experimental results demonstrate that this method outperforms the traditional single reward function mechanism in the pursuit scenario by enhancing agents’policy scores of the task.These ideas offer a solution to the convergence challenges faced by DRL models in long episode pursuit problems,leading to an improved model training performance.展开更多
目的观察分析中药药浴治疗寻常型银屑病的临床疗效。方法纳入2018年6月至2019年12月于上海市皮肤病医院就诊的144例寻常型银屑病患者为研究对象。根据纳入标准,最终入选141例患者,随机分为两组,试验组(n=71)采用复方青黛胶囊及中药药浴...目的观察分析中药药浴治疗寻常型银屑病的临床疗效。方法纳入2018年6月至2019年12月于上海市皮肤病医院就诊的144例寻常型银屑病患者为研究对象。根据纳入标准,最终入选141例患者,随机分为两组,试验组(n=71)采用复方青黛胶囊及中药药浴干预,对照组(n=70)采用复方青黛胶囊及麦饭石粉洗浴。观察记录患者皮损、银屑病面积、严重性指数评分(psoriasis area and severity index,PASI)及皮肤病生活质量指数(dermatology life of quality index,DLQI)变化。结果试验组患者愈显率为84.30%,对照组患者愈显率为63.20%,两组差异具有统计学意义(P<0.05);试验组总有效率为94.30%,对照组总有效率为85.30%,两组差异无统计学意义(P>0.05);试验组患者治疗后的PASI评分、DLQI评分明显优于对照组(P<0.05)。结论四草克银方药浴可改善银屑病血热证患者的临床症状。展开更多
基金National Natural Science Foundation of China(Nos.61803260,61673262 and 61175028)。
文摘Multi-agent reinforcement learning has recently been applied to solve pursuit problems.However,it suffers from a large number of time steps per training episode,thus always struggling to converge effectively,resulting in low rewards and an inability for agents to learn strategies.This paper proposes a deep reinforcement learning(DRL)training method that employs an ensemble segmented multi-reward function design approach to address the convergence problem mentioned before.The ensemble reward function combines the advantages of two reward functions,which enhances the training effect of agents in long episode.Then,we eliminate the non-monotonic behavior in reward function introduced by the trigonometric functions in the traditional 2D polar coordinates observation representation.Experimental results demonstrate that this method outperforms the traditional single reward function mechanism in the pursuit scenario by enhancing agents’policy scores of the task.These ideas offer a solution to the convergence challenges faced by DRL models in long episode pursuit problems,leading to an improved model training performance.
文摘目的观察分析中药药浴治疗寻常型银屑病的临床疗效。方法纳入2018年6月至2019年12月于上海市皮肤病医院就诊的144例寻常型银屑病患者为研究对象。根据纳入标准,最终入选141例患者,随机分为两组,试验组(n=71)采用复方青黛胶囊及中药药浴干预,对照组(n=70)采用复方青黛胶囊及麦饭石粉洗浴。观察记录患者皮损、银屑病面积、严重性指数评分(psoriasis area and severity index,PASI)及皮肤病生活质量指数(dermatology life of quality index,DLQI)变化。结果试验组患者愈显率为84.30%,对照组患者愈显率为63.20%,两组差异具有统计学意义(P<0.05);试验组总有效率为94.30%,对照组总有效率为85.30%,两组差异无统计学意义(P>0.05);试验组患者治疗后的PASI评分、DLQI评分明显优于对照组(P<0.05)。结论四草克银方药浴可改善银屑病血热证患者的临床症状。
