Enhancing deep reinforcement learning for scale flexibility in real-time strategy games

Real-time strategy (RTS) games present a unique challenge for AI agents due to the combination of several fundamental AI problems. While Deep Reinforcement Learning (DRL) has shown promise in the development of autonomous agents for the genre, existing architectures often struggle with games featuring maps of varying dimensions. This limitation hinders the agent’s ability to generalize its learned strategies across different scenarios. This paper proposes a novel approach that overcomes this problem by incorporating Spatial Pyramid Pooling (SPP) within a DRL framework. We leverage the GridNet architecture’s encoder–decoder structure and integrate an SPP layer into the critic network of the Proximal Policy Optimization (PPO) algorithm. This SPP layer dynamically generates a standardized representation of the game state, regardless of the initial observation size. This allows the agent to effectively adapt its decision-making process to any map configuration. Our evaluations demonstrate that the proposed method significantly enhances the model’s flexibility and efficiency in training agents for various RTS game scenarios, albeit with some discernible limitations when applied to very small maps. This approach paves the way for more robust and adaptable AI agents capable of excelling in sequential decision problems with variable-size observations

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Mucopolysaccharidosis I, II, and VI: Brief review and guidelines for treatment

Mucopolysaccharidoses (MPS) are rare genetic diseases caused by the deficiency of one of the lysosomal enzymes involved in the glycosaminoglycan (GAG) breakdown pathway. This metabolic block leads to the accumulation of GAG in various organs and tissues of the affected patients, resulting in a multisystemic clinical picture, sometimes including cognitive impairment. Until the beginning of the XXI century, treatment was mainly supportive. Bone marrow transplantation improved the natural course of the disease in some types of MPS, but the morbidity and mortality restricted its use to selected cases. The identification of the genes involved, the new molecular biology tools and the availability of animal models made it possible to develop specific enzyme replacement therapies (ERT) for these diseases. At present, a great number of Brazilian medical centers from all regions of the country have experience with ERT for MPS I, II, and VI, acquired not only through patient treatment but also in clinical trials. Taking the three types of MPS together, over 200 patients have been treated with ERT in our country. This document summarizes the experience of the professionals involved, along with the data available in the international literature, bringing together and harmonizing the information available on the management of these severe and progressive diseases, thus disclosing new prospects for Brazilian patients affected by these conditions

Educomunicação, Transformação Social e Desenvolvimento Sustentável

Esta publicação apresenta os principais trabalhos dos GTs do II Congresso Internacional de Comunicação e Educação nos temas Transformação social, com os artigos que abordam principalmente Educomunicação e/ou Mídia-Educação, no contexto de políticas de diversidade, inclusão e equidade; e, em Desenvolvimento Sustentável os artigos que abordam os avanços da relação comunicação/educação no contexto da educação ambiental e desenvolvimento sustentável