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For example, the outcome of a game (i.e., whether one player won or lost) can be easily measured without providing labeled examples of desired strategies. Neuroevolution is commonly used as part of the reinforcement learning paradigm, and it can be contrasted with conventional deep learning techniques that use backpropagation ( gradient descent ...
RUR - Python Learning Environment (RUR-PLE) is an educational tool to help students learn the Python programming language. Made by André Roberge. RUR-PLE uses the idea behind Karel the Robot, making the learning of Python programming more interesting. A student writes a program that controls a 'robot' that moves through a city consisting of a ...
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves training a reward model to represent preferences, which can then be used to train other models through reinforcement learning .
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised ...
Blue Brain Project, an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the molecular level. [1] Google Brain, a deep learning project part of Google X attempting to have intelligence similar or equal to human-level. [2] Human Brain Project, ten-year scientific research project, based on exascale ...
Learning can happen either through autonomous self-exploration or through guidance from a human teacher, like for example in robot learning by imitation. Robot learning can be closely related to adaptive control , reinforcement learning as well as developmental robotics which considers the problem of autonomous lifelong acquisition of ...
Asynchronous multi-body framework (AMBF) is an open-source 3D versatile simulator for robots developed in April 2019. This multi-body framework provides a real-time dynamic simulation of multi-bodies such as robots, free bodies, and multi-link puzzles, paired with real-time haptic interaction with various input devices. [1]
It also contains its own simulator written completely in Python. It can directly control a variety of real robots, including the Pioneer, Khepera, AIBO, and Hemisson. The ideas from PyroBot continue to evolve as Myro, short for My Robot, in the Institute for Personal Robots in Education software, although it is no longer for Python only. Myro ...