Machine learning, neural and statistical classification | Guide books skip to main content ACM
Digital Library home ACM home Google, Inc. (search) Advanced Search Browse About Sign in …

This paper describes recent experiments in automatically constructing reactive agents. The
method used is behavioural cloning, where the logged data from skilled, human operators …

Simulation is a crucial tool for accelerating the development of autonomous vehicles.
Making simulation realistic requires models of the human road users who interact with such …

We demonstrate the first large-scale application of model-based generative adversarial
imitation learning (MGAIL) to the task of dense urban self-driving. We augment standard …

Offline multi-agent reinforcement learning is challenging due to the coupling effect of both
distribution shift issue common in offline setting and the high dimension issue common in …

A common inference task consists of making a discrete prediction about some object given
other details about the object. For instance, in financial credit assessment as discussed by …

This paper describes experiments in applying inductive learning to the task of acquiring a
complex motor skill by observing human subjects. A flight simulation program has been …

Rule based detectors were used with a single cluster of accelerometers attached to the
shank for the real time detection of the main phases of normal gait during walking. The gait …

Reinforcement learning algorithms require many samples when solving complex
hierarchical tasks with sparse and delayed rewards. For such complex tasks, the recently …

Deep reinforcement learning holds significant potential for application in industrial decision-
making, offering a promising alternative to traditional physical models. However, its black …