Although the game is novel, and the completely mixed unique symmetric equilibrium is difficult to compute, people quickly learn to play close to it both in the field and laboratory. Standard models of belief-based learning and reinforcement learning are unable to account for the observed learning ...
简单来说同时学习多个任务, 可以让 imitation learning 更加容易. 同样考虑驾驶的例子, 我们考虑同时学习到达\boldsymbol{p}_1, \boldsymbol{p}_2, \ldots,\boldsymbol{p}_n等多个地点, 使用策略\pi_\theta(\boldsymbol{a} \mid \boldsymbol{s}, \boldsymbol{p}). 这样我们能够覆盖更多的数据, 包括完成...
Generative Adversarial Imitation Learning (GAIL) employs the generative adversarial learning framework for imitation learning and has shown great potentials. GAIL and its variants, however, are found highly sensitive to hyperparameters and hard to converge well in practice. One key issue is that the ...
Although the game is novel, and the completely mixed unique symmetric equilibrium is difficult to compute, people quickly learn to play close to it both in the field and laboratory. Standard models of belief-based learning and reinforcement learning are unable to account for the observed learning ...
and if the online learning has no regret, the agent can provably learn an expert-like policy. Online IL has demonstrated empirical successes in many applications and interestingly, its policy improvement speed observed in practice is usually much faster than existing theory suggests. In this work,...
This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input dynamics. We propose a model-free data-driven inverse reinforcement learning (RL) algorithm for a leaner to find the cost functions of aN-player Nash expert system given the expert’s states...
Python Course CS231nVideoEnsembleLearningZhihu Deeplearningwithout a phdVideo+CSDN+CodeD-S Evidence Theory Pdf 智能推荐 Generative Adversarial Imitation Learning 论文简析 《Generative Adversarial Imitation Learning》2016 1、几个概念: (1) occupancy measure ρπ(s,a): (2)cost function C(s,a), π策...
We observe an increase in the probability of convergence to equilibrium, as the incentives for optimal play become more pronounced. 展开 关键词: Theoretical or Mathematical/ behavioural sciences convergence decision theory economic cybernetics learning (artificial intelligence) probability/ imitation learning ...
So supervised learning theory and practice is very well understood. I think the challenge that the world has been focusing… or has a renewed focus on in the last five, ten years has been reinforcement learning, right? And reinforcement learning algorithms try to explo...
Paper Collection for Imitation Learning in RL with brief introductions. This collection refers toAwesome-Imitation-Learningand also contains self-collected papers. To be precise, the "imitation learning" is the general problem of learning from expert demonstration (LfD). There are 2 names derived fro...