This repository contains the implementation of the paper "Maximum Entropy Deep Inverse Reinforcement Learning" by Wulfmeier et al. [1] in PyTorch. You will also find in the notebooks directory a ...

Unleash Windows 11's hidden features, maximize the power of its AI tools, and fine-tune your PC like a pro with these ...

Abstract: Inverse reinforcement learning optimal control is under the framework of learner–expert, the learner system can learn expert system's trajectory and optimal control policy via a ...

ABSTRACT: The integration of artificial intelligence into the development and production of mechatronic products offers a substantial opportunity to enhance efficiency, adaptability, and system ...

Designing antibodies with high specificity and binding affinity to diverse therapeutic antigens remains a significant challenge in drug development. Current methods struggle to effectively generate ...

Large language models (LLMs) have gained significant attention in the field of artificial intelligence, primarily due to their ability to imitate human knowledge through extensive datasets. The ...

Abstract: Inverse optimal control (IOC) seeks to infer a control cost function that captures the underlying goals and preferences of expert demonstrations. While significant progress has been made in ...

This repository contains the source code to learn robot inverse dyanimcs models, based on the Lagrangian Inspired Polunomial (LIP) Kernal described in our IEEE TRO paper G. Giacomuzzo, R. Carli, D.