A type of artificial intelligence that focuses on designing systems that can learn from and make decisions based on data.
This paper presents a new approach to autonomous navigation using deep reinforcement learning (DRL). It addresses the issues of limited explainability and suboptimal performance in DRL by introducing three auxiliary…
Continue readingThe article discusses the development of a versatile, cost-effective robotic system named Dobb E which can learn and perform tasks in a home environment. The system learns new tasks in…
Continue readingThe article presents a new framework for single-source domain generalization in lane detection. This is important for autonomous vehicles to navigate and localize their position on the road. The framework…
Continue readingThis article introduces a hybrid approach for learning Human-Robot Interaction (HRI) from Human-Human Interactions (HHI). The method uses Hidden Markov Models (HMMs) as the latent space priors for a Variational…
Continue readingThe article discusses the challenges faced in finding equilibrium feedback control in two-player differential games due to the curse of dimensionality. It explores three potential solutions: a hybrid learning method,…
Continue readingDiffuseBot, as presented in this paper, is a revolutionary step in the field of soft robotics and virtual creature content creation. It leverages diffusion-based algorithms for the co-design of soft…
Continue readingThe paper discusses a novel Deep Reinforcement Learning (DRL) algorithm for designing optimal control policies for robots in unknown environments. The algorithm uses a mission-driven exploration strategy to prioritize exploration…
Continue readingThe paper introduces DPSUR, a new privacy-preserving machine learning framework that selectively updates and releases data during model training. This technique is designed to protect against privacy attacks such as…
Continue readingThe article discusses the use of blockchain technology to address data privacy and security issues in collaborative machine learning over Internet of Things (IoT) devices. Traditional centralized machine learning models…
Continue readingThis research paper presents PrivRecourse, a solution to the privacy issues that arise when generating realistic recourse paths based on instance-based counterfactual explanations. The system uses differentially private (DP) clustering…
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