This paper considers sustainable and cooperative behavior in multi-agent systems. In the proposed predator-prey simulation, multiple selfish predators can learn to act sustainably by maintaining a herd of reproducing prey and further hunt cooperatively for long term benefit. Since the predators face starvation pressure, the scenario can also turn in a tragedy of the commons if selfish individuals decide to greedily hunt down the prey population before their conspecifics do, ultimately leading to extinction of prey and predators. This paper uses Multi-Agent Reinforcement Learning to overcome a collapse of the simulated ecosystem, analyzes the impact factors over multiple dimensions and proposes suitable metrics. We show that up to three predators are able to learn sustainable behavior in form of collective herding under starvation pressure. Complex cooperation in form of group hunting emerges between the predators as their speed is handicapped and the prey is given more degrees of freedom to escape. The implementation of environment and reinforcement learning pipeline is available online. 1
Constrained optimization problems are usually translated to (naturally unconstrained) Ising formulations by introducing soft penalty terms for the previously hard constraints. In this work, we empirically demonstrate that assigning the appropriate weight to these penalty terms leads to an enlargement of the minimum spectral gap in the corresponding eigenspectrum, which also leads to a better solution quality on actual quantum annealing hardware. We apply machine learning methods to analyze the correlations of the penalty factors and the minimum spectral gap for six selected constrained optimization problems and show that regression using a neural network allows to predict the best penalty factors in our settings for various problem instances. Additionally, we observe that problem instances with a single global optimum are easier to optimize in contrast to ones with multiple global optima.
With increasing impact of hydrogen-based economy it is necessary to consider relevant hydrogen embrittlement effects and risks resulting from it. As higher gas pressures are in discussion, the use of higher steel strength levels as compared to existing pipelines appears reasonable. Clarifying the product requirements is necessary for safe operation. Lately, the interaction of pressurized hydrogen gas with steel has been studied more detailed. This allows more precise safety considerations for the transport of hydrogen gas. The results of laboratory trials of different semi-finished products (medium and large diameter line pipes, induction bent pipes) exposed to hydrogen gas will be used to clarify this point. Several laboratory test methods were selected, allowing to focus on local effects of hydrogen enrichment in conjunction with mechanical loads. Challenges when testing in high pressure hydrogen environment result mainly from the safety aspects to be respected, but also from precautions required to achieve reproducible test conditions and to avoid unwanted system contaminations. Substantiated test results indicate excellent behavior of the materials tested in terms of ductility and fracture toughness in high pressure hydrogen applications; all relevant ASME criteria for material selection are fully met. To support the ongoing discussion regarding hydrogen testing protocols and relevant material properties (toughness parameters) in both, qualification of components and design of pipelines, Salzgitter and its Steel Processing business units are planning further extended R&D studies.
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