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A current approach is multi-agent reinforcement learning (MARL), because the complexity of many tasks arising in complex domains makes it difficult to solve them with pre-programmed (single) agent behaviors, instead, agents can discover a solution on their own, using learning.
By deeply examining life history, including human evolution, we can discover proven solutions to surviving in a hostile and unpredictable world.
When the tracking is done during an exam, we can discover how students view WSIs.
We can discover things about the universe.
We can find a solution to addiction, too.
But, together, we usually discover a solution that we wouldn't have discovered if we were all stuck in our own little knowledge cubicles.
Only by engaging in collaborative discussions will we discover a solution that doesn't undermine the security of everyone.
It's all happening so fast that often, in the very moment in which we locate a problem, someone else discovers a solution.
Some students dissatisfied with their writing scores have discovered a solution: They can pay ACT $50 to re-score their essay.
By calculating a newly defined ParaRate, the proposed methodology can discover alternative solutions that may possess high possibilities of replacing original genes at each node within a pathway without losing biological function.
When we discover a new solution, we tend to stick with it.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com