While reinforcement learning (RL) achieves tremendous success in sequential decision-
making problems of many domains, it still faces key challenges of data inefficiency and the …

In this article, we investigate the role of causal reasoning in robotics research. Inspired by a
categorization of human causal cognition, we propose a categorization of robot causal …

作为机器人技能学习中的一个重要分支, 模仿学习近年来在机器人系统中得到了广泛的应用.
模仿学习能够将人类的技能以一种相对直接的方式迁移到机器人系统中, 其思路是先从少量示教 …

Exploiting robots for activities in human-shared environments, whether warehouses,
shopping centres or hospitals, calls for such robots to understand the underlying physical …

While the concept of a conscious machine is intriguing, producing such a machine remains
controversial and challenging. Here, we describe how our work on creating a humanoid …

Reconstructing accurate causal models of dynamic systems from time-series of sensor data
is a key problem in many real-world scenarios. In this paper, we present an overview based …

Assisting humans in collaborative tasks is a promising application for robots, however
effective assistance remains challenging. In this article, we propose a method for providing …

The field of artificial consciousness (AC) has largely developed outside of mainstream
artificial intelligence (AI), with separate goals and criteria for success and with only a …

Deploying robots in human-shared spaces requires understanding interactions among
nearby agents and objects. Modelling cause-and-effect relations through causal inference …

Identifying the main features and learning the causal relationships of a dynamic system from
time-series of sensor data are key problems in many real-world robot applications. In this …