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Learning to Imitate

Introduce a simple, stable, and data-efficient framework for learning via imitation of a few experts ....

Jacob Schreiber , Mo Tiwari , Stuart Russel , Brad Porter , Ikuno Kim , Megha Srivastava , Susanr Qi , Sidd Karamcheti , Skanda Vaidyanath , Artificial Intelligence , Inverseq Learning , Behavioral Cloning , Dataset Aggregation , Inverse Reinforcement Learning , Imitation Approaches , Adversarial Imitation Learning , Adversarial Imitation , Carracing Gym , Stefano Ermon ,

Decision Transformer: Unifying sequence modelling and model-free, offline RL

Decision Transformer: Unifying sequence modelling and model-free, offline RL
Tue, 01 Jun 2021
By
In this article we will explain and discuss the paper:
that explores application of transformers to model sequential decision making problems - formalized as Reinforcement Learning (RL). By training a language model on a training dataset of random walk trajectories, it can figure out optimal trajectories by just conditioning on a large reward.
Figure 1. Conditioned on a starting state and generating largest possible return at each node, Decision Transformer sequences optimal paths. (Source)
The idea is simple. 1) Each modality (return, state, or action) is passed into an embedding network (convolutional encoder for images, linear layer for continuous states). 2) embeddings are processed by an autoregressive transformer model, trained to predict the next action given the previous tokens using a linear output layer. ....

Neural Network , Decision Transformer , Reinforcement Learning , Conservativeq Learing , Random Ensemble Mixture , Quantile Regression Deepq Network , Computer Vision , Vision Transformer , Markov Decision Process , Transformer Pseudocode , Behavioral Cloning , Conservativeq Learning , Back Propagation Though Time , Temporal Difference , State Action Value , Percentile Behavior Cloning , Deep Neural Network , நரம்பியல் வலைப்பின்னல் , வலுவூட்டல் கற்றல் , கணினி பார்வை , பார்வை மின்மாற்றி , மார்க்கோவ் முடிவு ப்ரோஸெஸ் , தற்காலிக வித்தியாசம் , ஆழமான நரம்பியல் வலைப்பின்னல் ,