Contemporary undertakings provide limitless opportunities for widespread application of machine reasoning and artificial intelligence in situations characterised by uncertainty, hostility and sheer volume of data. The paper develops a valuation network as a graphical system for higher-level fusion and reasoning under uncertainty in support of the human operators. Valuations, which are mathematical representation of (uncertain) knowledge and collected data, are expressed as credal sets, defined as coherent interval probabilities in the framework of imprecise probability theory. The basic operations with such credal sets, combination and marginalisation, are defined to satisfy the axioms of a valuation algebra. A practical implementation of the credal valuation network is discussed and its utility demonstrated on a small scale example.
翻译:当代企业为在不确定、敌对和数据数量庞大的情况下广泛应用机器推理和人工智能提供了无限机会。本文开发了一个估值网络,作为支持人类操作者而不确定的更高层次聚合和推理的图形系统。估值是(不确定)知识和所收集数据的数学表示,其表述为信用组合,定义为不精确概率理论框架内的连贯的间隔概率。这些临界组合、组合和边缘化的基本操作的定义是满足估值代数的学理。讨论了验证估值网络的实际实施情况,并用小型实例展示了其实用性。