Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology
A critical aspect of evolution is the layer of developmental physiology that operates between
the genotype and the anatomical phenotype. While much work has addressed the evolution …
the genotype and the anatomical phenotype. While much work has addressed the evolution …
Neuroevolution: from architectures to learning
Artificial neural networks (ANNs) are applied to many real-world problems, ranging from
pattern classification to robot control. In order to design a neural network for a particular task …
pattern classification to robot control. In order to design a neural network for a particular task …
[ספר][B] The alignment problem: How can machines learn human values?
B Christian - 2021 - books.google.com
'Vital reading. This is the book on artificial intelligence we need right now.'Mike Krieger,
cofounder of Instagram Artificial intelligence is rapidly dominating every aspect of our …
cofounder of Instagram Artificial intelligence is rapidly dominating every aspect of our …
Embodied intelligence via learning and evolution
The intertwined processes of learning and evolution in complex environmental niches have
resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal …
resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal …
Human-level performance in 3D multiplayer games with population-based reinforcement learning
Reinforcement learning (RL) has shown great success in increasingly complex single-agent
environments and two-player turn-based games. However, the real world contains multiple …
environments and two-player turn-based games. However, the real world contains multiple …
Weight agnostic neural networks
Not all neural network architectures are created equal, some perform much better than
others for certain tasks. But how important are the weight parameters of a neural network …
others for certain tasks. But how important are the weight parameters of a neural network …
Alphastar: An evolutionary computation perspective
In January 2019, DeepMind revealed AlphaStar to the world---the first artificial intelligence
(AI) system to beat a professional player at the game of StarCraft II---representing a …
(AI) system to beat a professional player at the game of StarCraft II---representing a …
On the expressivity of markov reward
Reward is the driving force for reinforcement-learning agents. This paper is dedicated to
understanding the expressivity of reward as a way to capture tasks that we would want an …
understanding the expressivity of reward as a way to capture tasks that we would want an …
Evolution-guided policy gradient in reinforcement learning
Abstract Deep Reinforcement Learning (DRL) algorithms have been successfully applied to
a range of challenging control tasks. However, these methods typically suffer from three core …
a range of challenging control tasks. However, these methods typically suffer from three core …
Evolved policy gradients
We propose a metalearning approach for learning gradient-based reinforcement learning
(RL) algorithms. The idea is to evolve a differentiable loss function, such that an agent …
(RL) algorithms. The idea is to evolve a differentiable loss function, such that an agent …