摘要
人工智能追求的长期目标是使机器能像人一样学习和思考。由于人类面临的许多问题具有不确定性、脆弱性和开放性,任何智能程度的机器都无法完全取代人类,这就需要将人的作用或人的认知模型引入到人工智能系统中,形成混合-增强智能的形态,这种形态是人工智能或机器智能的可行的、重要的成长模式。混合-增强智能可以分为两类基本形式:一类是人在回路的人机协同混合增强智能,另一类是将认知模型嵌入机器学习系统中,形成基于认知计算的混合智能。本文讨论人机协同的混合-增强智能的基本框架,以及基于认知计算的混合-增强智能的基本要素:直觉推理与因果模型、记忆和知识演化;特别论述了直觉推理在复杂问题求解中的作用和基本原理,以及基于记忆与推理的视觉场景理解的认知学习网络;阐述了竞争-对抗式认知学习方法,并讨论了其在自动驾驶方面的应用;最后给出混合-增强智能在相关领域的典型应用。
The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models: one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.
基金
Project supported by the Chinese Academy of Engi- neering, the National Natural Science Foundation of China (No. L1522023), the National Basic Research Program (973) of China (No. 2015CB351703), and the National Key Research and Development Plan (Nos. 2016YFB1001004 and 2016YFB1000903)
关键词
人-机协同
混合增强智能
认知计算
直觉推理
因果模型
认知映射
视觉场景理解
自主驾驶汽车
Human-machine collaboration
Hybrid-augmented intelligence
Cognitive computing
Intuitivereasoning
Causal model
Cognitive mapping
Visual scene understanding
Self-driving cars