A Study of AI Population Dynamics with Million-agent Reinforcement Learning

We conduct an empirical study on discovering the ordered collective dynamics obtained by a population of intelligence agents, driven by million-agent reinforcement learning. Our intention is to put intelligent agents into a simulated natural context and verify if the principles developed in the real world could also be used in understanding an artificially-created intelligent population. To achieve this, we simulate a large-scale predator-prey world, where the laws of the world are designed by only the findings or logical equivalence that have been discovered in nature. We endow the agents with the intelligence based on deep reinforcement learning (DRL). In order to scale the population size up to millions agents, a large-scale DRL training platform with redesigned experience buffer is proposed. Our results show that the population dynamics of AI agents, driven only by each agent's individual self-interest, reveals an ordered pattern that is similar to the Lotka-Volterra model studied in population biology. We further discover the emergent behaviors of collective adaptations in studying how the agents' grouping behaviors will change with the environmental resources. Both of the two findings could be explained by the self-organization theory in nature.Comment: Full version of the paper presented at AAMAS 2018 (International Conference on Autonomous Agents and Multiagent Systems

Tetra­kis(μ-naphthalene-1-acetato-κ2 O:O′)bis­[(N,N-dimethyl­formamide-κO)copper(II)]

The asymmetric unit of the title compound, [Cu2(C12H9O2)4(C3H7NO)2], contains two independent centrosymmetric dinuclear copper(II) complexes. The central paddle-wheel units are formed by four bridging bidentate naphthalene-1-acetate ligands with two dimethyl­formamide ligands in the axial positions. The unique CuII ions have slightly distorted square-pyramidal coordination geometries. One of the naphthalene rings is disordered over two sets of sites, with refined occpancies of 0.535 (4) and 0.465 (4)

Exposure to crude microcystins via intraperitoneal injection, but not oral gavage, causes hepatotoxicity in ducks

Recently, large-scale cyanobacterial blooms have occurred in fishponds near the suburbs of Xinxiang City in China. The present study aimed to identify the cyanobacterial blooms in the fishpond and evaluate their toxicity on ducks via intraperitoneal injection or oral exposure (gavage) of crude microcystins obtained from the scum of cyanobacterial bloom. The results of the acute toxicity tests showed that intraperitoneal injection of crude microcystin solution caused hepatotoxicity in ducks and ducklings, but oral exposure failed to do so. This result confirms the observation of no duck intoxication by a natural way of oral exposure in the fishponds during the periods of blooms. In addition, subchronic exposure of microcystins by intraperitoneal injection significantly inhibited the growth of ducklings.Keywords: Microcystis bloom, microcystins, duck, toxicit

Study on Law of Personnel Evacuation in Deep Buried Metro Station Based on the Characteristics of Fire Smoke Spreading

AbstractWith the improvement of people's life and the rapid development of urban traffic, the subway has the advantages of convenience and celerity, to a large extent, which greatly eases the traffic congestion phenomenon. With the attendant, the safety of the subway environment becomes vital. Many engineers focus on the study of the fire prevention and safety to escape. In this paper, a comprehensive study on the fire smoke spreading and the evacuation of the people in the deep buried metro model is carried out. First, the deep buried metro model is modeled on the STEPS software, and the personnel evacuation rule is obtained. According to the evacuation situation, the corresponding fire smoke monitoring points are built in the fire scenario which is set up on FDS+Evac software. Then, FDS+Evac program is used to simulate the evacuation in a fire scenario. It has not only analyzed the real time effect that the characteristics of fire smoke spread have on the personnel evacuation, but also improved the accuracy of the subway fire safety evaluation

Transcriptome Sequencing in a Tibetan Barley Landrace with High Resistance to Powdery Mildew

Hulless barley is an important cereal crop worldwide, especially in Tibet of China. However, this crop is usually susceptible to powdery mildew caused by Blumeria graminis f. sp. hordei. In this study, we aimed to understand the functions and pathways of genes involved in the disease resistance by transcriptome sequencing of a Tibetan barley landrace with high resistance to powdery mildew. A total of 831 significant differentially expressed genes were found in the infected seedlings, covering 19 functions. Either “cell,” “cell part,” and “extracellular region” in the cellular component category or “binding” and “catalytic” in the category of molecular function as well as “metabolic process” and “cellular process” in the biological process category together demonstrated that these functions may be involved in the resistance to powdery mildew of the hulless barley. In addition, 330 KEGG pathways were found using BLASTx with an E-value cut-off of <10−5. Among them, three pathways, namely, “photosynthesis,” “plant-pathogen interaction,” and “photosynthesis-antenna proteins” had significant matches in the database. Significant expressions of the three pathways were detected at 24 h, 48 h, and 96 h after infection, respectively. These results indicated a complex process of barley response to powdery mildew infection