Non alcoholic fatty liver disease (NAFLD) is the most common cause of ch...
Real-world games, which concern imperfect information, multiple players,...
Recently, anchor-based trajectory prediction methods have shown promisin...
Multi-agent reinforcement learning (MARL) has achieved remarkable succes...
Task-agnostic cross-domain pre-training shows great potential in image-b...
Unmanned combat air vehicle (UCAV) combat is a challenging scenario with...
The latent world model provides a promising way to learn policies in a
c...
This paper aims to tackle the interactive behavior prediction task, and
...
Communication-based multi-agent reinforcement learning (MARL) provides
i...
Realistic and diverse simulation scenarios with reactive and feasible ag...
Multi-agent reinforcement learning methods such as VDN, QMIX, and QTRAN ...
Multi-task intersection navigation including the unprotected turning lef...
Recent works have demonstrated that transformer can achieve promising
pe...
Different from other deep scalable architecture based NAS approaches, Br...
In single-agent Markov decision processes, an agent can optimize its pol...
In recent years, control under urban intersection scenarios becomes an
e...
The development of autonomous driving has attracted extensive attention ...
Communicating with each other in a distributed manner and behaving as a ...
Recently, Tensor Ring Networks (TRNs) have been applied in deep networks...
Existing model-based value expansion methods typically leverage a world ...
In order to further improve the search efficiency of Neural Architecture...
This paper investigates the automatic exploration problem under the unkn...
A good object segmentation should contain clear contours and complete
re...
Multi-sensor fusion-based road segmentation plays an important role in t...
Although Neural Architecture Search (NAS) can bring improvement to deep
...
The Fighting Game AI Competition (FTGAIC) provides a challenging benchma...
Efficient Neural Architecture Search (ENAS) achieves novel efficiency fo...
Semantic segmentation with deep learning has achieved great progress in
...
Deep reinforcement learning (DRL) has made great achievements since prop...
Autonomous driving decision-making is a great challenge due to the compl...
This paper investigates the vision-based autonomous driving with deep
le...
Real-time strategy games have been an important field of game artificial...