A young Chinese explorer is determined to raise public awareness about climate change and involve more young people in creating a sustainable future.PARTIES to the United Nations(UN)Framework Convention on Climate Cha...A young Chinese explorer is determined to raise public awareness about climate change and involve more young people in creating a sustainable future.PARTIES to the United Nations(UN)Framework Convention on Climate Change met in Glasgow,United Kingdom,for the convention’s 26th Conference of Parties(COP26)from October 31 to November 12,2021.Representatives of countries from around the world negotiated for a concerted global response to one of the most urgent challenges of our time.展开更多
The Presidential Decree signed on February 7. 2017, approved the Strategy for Actions for the Development of the Republic of Uzbekistan along Five Priority Areas in 2017-2021, and worked out on the basis of a comprehe...The Presidential Decree signed on February 7. 2017, approved the Strategy for Actions for the Development of the Republic of Uzbekistan along Five Priority Areas in 2017-2021, and worked out on the basis of a comprehensive study of pressing issues of the population.展开更多
Many countries are developing national strategies and action plans aimed at minimising the negative impacts of climate change on biodiversity.The purpose of this paper is to provide a brief overview not only of strate...Many countries are developing national strategies and action plans aimed at minimising the negative impacts of climate change on biodiversity.The purpose of this paper is to provide a brief overview not only of strategies and plans that have been developed in Australia,but also of research that has been carried out in Australia by the Commonwealth Scientific and Industrial Research Organisation(CSIRO) Climate Adaptation Flagship to assist the development of future strategies and plans.Major points are summarised from key policy documents such as the National Biodiversity and Climate Change Action Plan 2004-2007,and Australia's Biodiversity Conservation Strategy 2010-2030,as well as the 2009 report on "Australia's Biodiversity and Climate Change".Within the first three years of its existence,the Natural Ecosystems theme in CSIRO Climate Adaptation Flagship has carried out studies analysing impacts and identifying potential adaptations across the whole of Australia's vast terrestrial and marine environments.Techniques used in these studies could be applied easily in other countries and could assist the development of more effective national strategies and adaptation action plans for the conservation of biodiversity under climate change.展开更多
China is severely impacted by desertification. Of its territory, 34,6% -- some 3.32 million km2 -- is classified as drylands （including arid, semi-arid and semi-humid arid areas）. Of the drylands, 2.62 million km2 m...China is severely impacted by desertification. Of its territory, 34,6% -- some 3.32 million km2 -- is classified as drylands （including arid, semi-arid and semi-humid arid areas）. Of the drylands, 2.62 million km2 meets the UNCCD definition of desertified land. These desertified lands spread across 18 provinces and account for 27.33% of the country＇s landmass. Over 400 million residents are affected, causing an annual direct economic loss exceed 64 billion CNY. China＇s desertification mitigation began in late 1950s. Through a number of high-profile programs ＂Three-North Shelterbelt Development Program＂, ＂National Program on Combating Desertification＂, ＂Sandification Control Program for Beijing and Tianjin Vicinity＂, and ＂Croplands to Forests or Grasslands Program＂ launched between 1978 and 2000, the Government of China has poured on average 0.024% of the country＇s annual GDP into desertiflcation mitigation and, as a result, some 20% of desertified lands have been brought under control. Approximately 50×104 km2 of the existing desertified lands are considered restorable given current technology. When the potential desertification increments induced by global warming are taken into account, total desertifled area within planning horizon is projected to range from 55×104 to 100×104 km2. With the approximate restoration rate of 1.5×104-2.2×104 km2 y-1, China＇s anti-desertification battle is expected to last 45-70 years. The current strategic plans set restoration targets at 22×104 km2 by 2015, with an additional 33×104 km2 by 2030, and the fnal 45×104 km2 of the 100×104 km2 restored by 2050. Through examining state investment in mitigation and current rehabilitation strategies, the paper recommends： （i） boardening the previous sectoral perspective to a multi-stakeholder approach; （ii） setting priority zones within the restorable area, and establishing National Special Eco-Zones; （iii） steering state investment from government investment in tree plantations to acquisition of planted/greened areas; and （iv） introducing preferential policies in favor of sandy land restoration, including extending land tenures to 70 years and compensating for ecological services.展开更多
The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the suffic...The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the sufficient market information to derive an optimal bidding strategy.However,this assumption may not be true in reality,particularly when a power market is newly launched.To help power suppliers bid with the limited information,a modified continuous action reinforcement learning automata algorithm is proposed.This algorithm introduces the discretization and Dyna structure into continuous action reinforcement learning automata algorithm for easy implementation in a repeated game.Simulation results verify the effectiveness of the proposed learning algorithm.展开更多
Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attack...Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.展开更多
文摘A young Chinese explorer is determined to raise public awareness about climate change and involve more young people in creating a sustainable future.PARTIES to the United Nations(UN)Framework Convention on Climate Change met in Glasgow,United Kingdom,for the convention’s 26th Conference of Parties(COP26)from October 31 to November 12,2021.Representatives of countries from around the world negotiated for a concerted global response to one of the most urgent challenges of our time.
文摘The Presidential Decree signed on February 7. 2017, approved the Strategy for Actions for the Development of the Republic of Uzbekistan along Five Priority Areas in 2017-2021, and worked out on the basis of a comprehensive study of pressing issues of the population.
文摘Many countries are developing national strategies and action plans aimed at minimising the negative impacts of climate change on biodiversity.The purpose of this paper is to provide a brief overview not only of strategies and plans that have been developed in Australia,but also of research that has been carried out in Australia by the Commonwealth Scientific and Industrial Research Organisation(CSIRO) Climate Adaptation Flagship to assist the development of future strategies and plans.Major points are summarised from key policy documents such as the National Biodiversity and Climate Change Action Plan 2004-2007,and Australia's Biodiversity Conservation Strategy 2010-2030,as well as the 2009 report on "Australia's Biodiversity and Climate Change".Within the first three years of its existence,the Natural Ecosystems theme in CSIRO Climate Adaptation Flagship has carried out studies analysing impacts and identifying potential adaptations across the whole of Australia's vast terrestrial and marine environments.Techniques used in these studies could be applied easily in other countries and could assist the development of more effective national strategies and adaptation action plans for the conservation of biodiversity under climate change.
基金supported by State Forestry Administration "Public Welfare Research Foundation" (No.201004010)"948 Program"(No.2008-4-47)
文摘China is severely impacted by desertification. Of its territory, 34,6% -- some 3.32 million km2 -- is classified as drylands （including arid, semi-arid and semi-humid arid areas）. Of the drylands, 2.62 million km2 meets the UNCCD definition of desertified land. These desertified lands spread across 18 provinces and account for 27.33% of the country＇s landmass. Over 400 million residents are affected, causing an annual direct economic loss exceed 64 billion CNY. China＇s desertification mitigation began in late 1950s. Through a number of high-profile programs ＂Three-North Shelterbelt Development Program＂, ＂National Program on Combating Desertification＂, ＂Sandification Control Program for Beijing and Tianjin Vicinity＂, and ＂Croplands to Forests or Grasslands Program＂ launched between 1978 and 2000, the Government of China has poured on average 0.024% of the country＇s annual GDP into desertiflcation mitigation and, as a result, some 20% of desertified lands have been brought under control. Approximately 50×104 km2 of the existing desertified lands are considered restorable given current technology. When the potential desertification increments induced by global warming are taken into account, total desertifled area within planning horizon is projected to range from 55×104 to 100×104 km2. With the approximate restoration rate of 1.5×104-2.2×104 km2 y-1, China＇s anti-desertification battle is expected to last 45-70 years. The current strategic plans set restoration targets at 22×104 km2 by 2015, with an additional 33×104 km2 by 2030, and the fnal 45×104 km2 of the 100×104 km2 restored by 2050. Through examining state investment in mitigation and current rehabilitation strategies, the paper recommends： （i） boardening the previous sectoral perspective to a multi-stakeholder approach; （ii） setting priority zones within the restorable area, and establishing National Special Eco-Zones; （iii） steering state investment from government investment in tree plantations to acquisition of planted/greened areas; and （iv） introducing preferential policies in favor of sandy land restoration, including extending land tenures to 70 years and compensating for ecological services.
基金This work was supported by the National Natural Science Foundation of China(No.U1866206).
文摘The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the sufficient market information to derive an optimal bidding strategy.However,this assumption may not be true in reality,particularly when a power market is newly launched.To help power suppliers bid with the limited information,a modified continuous action reinforcement learning automata algorithm is proposed.This algorithm introduces the discretization and Dyna structure into continuous action reinforcement learning automata algorithm for easy implementation in a repeated game.Simulation results verify the effectiveness of the proposed learning algorithm.
文摘Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.
