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Mixed Motive Settings

cooperativeai.com · 4,787 words · saved by 1 readers

As mentioned in the introductory section, cooperative AI uses many tools and concepts from game theory, a mathematical framework for modelling strategic interactions. In this section, we’ll introduce you to some of the most important tools and concepts, and use these to get a sense for the kind of problems, settings and systems that the field of cooperative AI tends to focus on, and why. Tooltip Text ‍ In game theory, multi-agent settings can be classified into three categories: ‍ ‍ Virtually all interactions you have with other human beings could be described as mixed-motive. In a family, a sports team, a classroom or a workplace you will have different people with different goals that are not perfectly aligned with each other, but neither perfectly opposed. ‍ Fully cooperative and fully competitive settings are popular research topics in AI (for example, some of the most talked about breakthroughs in recent AI history are to do with performance in zero-sum games like Go). There are m

Curriculum Curriculum As mentioned in the introductory section, cooperative AI uses many tools and concepts from game theory, a mathematical framework for modelling strategic interactions. In this section, we’ll introduce you to some of the most important tools and concepts, and use these to get a sense for the kind of problems, settings and systems that the field of cooperative AI tends to focus on, and why. Tooltip Text Learning Objectives: Distinguish between fully cooperative, fully competitive, and mixed-motive settings, and explain why most real-world interactions fall along a…

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