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Alife Machine Learning System and Method

机译:Alife机器学习系统和方法

摘要

Roughly described, a problem solving platform distributes the solving of the problem over a evolvable individuals, each of which also evolves its own pool of actors. The actors have the ability to contribute collaboratively to a solution at the level of the individual, instead of each actor being a candidate for the full solution. Populations evolve both at the level of the individual and at the level of actors within an individual. In an embodiment, an individual defines parameters according to which its population of actors can evolve. The individual is fixed prior to deployment to a production environment, but its actors can continue to evolve and adapt while operating in the production environment. Thus a goal of the evolutionary process at the level of individuals is to find populations of actors that can sustain themselves and survive, solving a dynamic problem for a given domain as a consequence.
机译:粗略地描述,一个问题解决平台将问题的解决分布在一个不断发展的个人上,每个人都在发展自己的参与者。参与者有能力在个人层面上共同为解决方案做出贡献,而不是每个参与者都是完整解决方案的候选人。人口不仅在个人层面而且在个人内的行为者层面发展。在一个实施例中,个体定义参数,根据该参数其行为者群体可以进化。个体在部署到生产环境之前是固定的,但是其参与者可以在生产环境中操作时继续发展和适应。因此,从个体的角度出发,进化过程的目标是找到可以维持自身生存和生存的演员群体,从而解决给定领域的动态问题。

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