Simulation is an appealing option for validating the safety of autonomous vehicles. Generative Adversarial Imitation Learning (GAIL) has recently been shown to learn representative human driver models. These human driver models were learned through training in single-agent environments, but they have difficulty in generalizing to multi-agent driving scenarios. We argue these difficulties arise ...

BACKGROUND The objective was to compare women's personal estimates of their risk with objective breast cancer risk estimates and to describe the risk factors for breast cancer identified by women. METHODS Telephone survey of a random sample of 761 rural and urban women with no history of breast cancer. Survey instrument included measures of perceptions of lifetime risk for breast cancer for t...

The default ARTMAP algorithm and its parameter values specified here define a ready-to-use general-purpose neural network system for supervised learning and recognition.

INTRODUCTION The tumor suppressor genes RASSF1A, APC, H-cadherin, RARbeta2, and cyclin D2 are methylated more frequently in breast cancer than in adjacent benign tissue. However, it is unclear whether promoter methylation of tumor suppressor genes in benign breast tissue is associated with an increased risk for breast cancer. METHODS Promoter hypermethylation was measured in benign and malign...

We present an approach for mobile robots to learn to navigate in pedestrian-rich environments via raw depth inputs, in a social-compliant manner. To achieve this, we adopt a generative adversarial imitation learning (GAIL) strategy for motion planning, which improves upon a supervised policy model pre-trained via behavior cloning. Our approach overcomes the disadvantages of previous methods, as...

This paper presents our ideas on generating formative feedback in the Genetics Argumentation Inquiry Learning (GAIL) system. GAIL will provide undergraduate biology students with tools for constructing Toulmin-style arguments on questions in genetics. Feedback will be based in part on the output of GAIL’s argument analyzer, which will compare learner arguments to automatically constructed exper...

With the development of AI, intelligence level vehicles is increasing. Structured roads, as common and important traffic scenes, are most typical application scenarios for realizing autonomous driving. The driving behavior decision-making intelligent has always been a controversial difficult research topic. Currently, mainstream methods, which mainly based on rules, lack adaptability generaliza...