597,055 research outputs found

    Optimistic Planning for Markov Decision Processes

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    International audienceThe reinforcement learning community has recently intensified its interest in online planning methods, due to their relative independence on the state space size. However, tight near-optimality guarantees are not yet available for the general case of stochastic Markov decision processes and closed-loop, state-dependent planning policies. We therefore consider an algorithm related to AO* that optimistically explores a tree representation of the space of closed-loop policies, and we analyze the near-optimality of the action it returns after n tree node expansions. While this optimistic planning requires a finite number of actions and possible next states for each transition, its asymptotic performance does not depend directly on these numbers, but only on the subset of nodes that significantly impact near-optimal policies. We characterize this set by introducing a novel measure of problem complexity, called the near-optimality exponent. Specializing the exponent and performance bound for some interesting classes of MDPs illustrates the algorithm works better when there are fewer near-optimal policies and less uniform transition probabilities

    Optimistic Planning for Markov Decision Processes

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    International audienceThe reinforcement learning community has recently intensified its interest in online planning methods, due to their relative independence on the state space size. However, tight near-optimality guarantees are not yet available for the general case of stochastic Markov decision processes and closed-loop, state-dependent planning policies. We therefore consider an algorithm related to AO* that optimistically explores a tree representation of the space of closed-loop policies, and we analyze the near-optimality of the action it returns after n tree node expansions. While this optimistic planning requires a finite number of actions and possible next states for each transition, its asymptotic performance does not depend directly on these numbers, but only on the subset of nodes that significantly impact near-optimal policies. We characterize this set by introducing a novel measure of problem complexity, called the near-optimality exponent. Specializing the exponent and performance bound for some interesting classes of MDPs illustrates the algorithm works better when there are fewer near-optimal policies and less uniform transition probabilities

    The Implicit Price of Urban Public Parks and Greenways: A Spatial-Contextual Approach

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    This is an Author's Original Manuscript of an article submitted for consideration in the Journal of Environmental Planning and Management [copyright Taylor & Francis]; Journal of Environmental Planning and Management is available online at http://www.tandfonline.com/This paper examines the value residents place on public parks in a mid-sized urban area. The analysis makes a direct contribution to the literature by examining the extent to which spatial and neighborhood context is related to the house price premium or discount associated with public recreational opportunities, natural resource areas, and urban greenways. The analysis shows that the value of public parks and greenways varies across space, neighborhood context, and park type. Community area fixed-effects are included to bolster the findings. The findings indicate that park and greenway investment should be planned and managed contextually in urban areas. Park planners can use these findings to inform public policy debates over park investment and, perhaps, support efforts focused on comprehensive neighborhood planning

    Preserving Comics Programming During Times of Institutional Change

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    Library comics conventions are opportunities to build community, promote collections, and cultivate joy. Before the COVID-19 pandemic, Oregon State University’s Valley Library had just started exploring ways to connect our campus with the Pacific Northwest’s vibrant comics scene. Although we scrapped our original plans, we were able to adapt by researching alternative programming, strengthening our community relationships, and planning for the future. Valley Library’s comic book programming was further impacted by a hiring freeze and the departure of several major comics programming boosters. Ultimately, we continued the collection development project that was previously intended to launch on Free Comic Book Day. We also investigated online conventions and continued to review literature for advice on creating the best possible in-person events for the future. While the last few years severely challenged the limits of normal, making space for joy and community has provided a helpful boost for students, faculty, and librarians

    Radiation modeling in the Earth and Mars atmospheres using LRO/CRaTER with the EMMREM Module

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    Abstract We expand upon the efforts of Joyce et al. (2013), who computed the modulation potential at the Moon using measurements from the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) instrument on the Lunar Reconnaissance Orbiter (LRO) spacecraft along with data products from the Earth-Moon-Mars Radiation Environment Module (EMMREM). Using the computed modulation potential, we calculate galactic cosmic ray (GCR) dose and dose equivalent rates in the Earth and Mars atmospheres for various altitudes over the course of the LRO mission. While we cannot validate these predictions by directly comparable measurement, we find that our results conform to expectations and are in good agreement with the nearest available measurements and therefore may be used as reasonable estimates for use in efforts in risk assessment in the planning of future space missions as well as in the study of GCRs. PREDICCS (Predictions of radiation from REleASE, EMMREM, and Data Incorporating the CRaTER, COSTEP, and other solar energetic particles measurements) is an online system designed to provide the scientific community with a comprehensive resource on the radiation environments of the inner heliosphere. The data products shown here will be incorporated into PREDICCS in order to further this effort and daily updates will be made available on the PREDICCS website (http://prediccs.sr.unh.edu). Key Points We model GCR dose and dose equivalent rates in Earth and Mars atmospheres Dose rates are in reasonable agreement with nearby measurements Data products will soon be made available on PREDICCS website

    Beyond markets: envisions of expanding public events in markets

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    The municipal markets network in Barcelona is unique in the world. It is made up of 39 food markets and 4 non-food markets. However, the traditional markets they represent are now facing the challenges of a new era. Today, less residents go to the markets for the promotion of supermarkets and shopping online. Moreover, the limited open time of markets also has influence. The article tries to explore more possibilities of the old municipal markets network in Barcelona. For the specific function of these buildings, they are arranged to be accessible for most of the residence in the city. This is valuable and a key factor for being public space. Therefore, if they are not efficiently used for trading, what else can they be used for? A proposal for renovating an old market and planning a new market is presented, which tries to mix more function for public use with the markets and make it the center of community again. Furthermore, these mix-used buildings can also be the urban catalysts which activate the neighbourhood space
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