Behavioural cloning
12 papers with code • 0 benchmarks • 2 datasets
Benchmarks
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Libraries
Use these libraries to find Behavioural cloning models and implementationsMost implemented papers
A Divergence Minimization Perspective on Imitation Learning Methods
We present $f$-MAX, an $f$-divergence generalization of AIRL [Fu et al., 2018], a state-of-the-art IRL method.
Augmented Behavioral Cloning from Observation
Imitation from observation is a computational technique that teaches an agent on how to mimic the behavior of an expert by observing only the sequence of states from the expert demonstrations.
Imitating Unknown Policies via Exploration
Behavioral cloning is an imitation learning technique that teaches an agent how to behave through expert demonstrations.
Counter-Strike Deathmatch with Large-Scale Behavioural Cloning
This paper describes an AI agent that plays the popular first-person-shooter (FPS) video game `Counter-Strike; Global Offensive' (CSGO) from pixel input.
Action Advising with Advice Imitation in Deep Reinforcement Learning
Action advising is a peer-to-peer knowledge exchange technique built on the teacher-student paradigm to alleviate the sample inefficiency problem in deep reinforcement learning.
Self-Supervised Adversarial Imitation Learning
We address this limitation by incorporating a discriminator into the original framework, offering two key advantages and directly solving a learning problem previous work had.
Deep attention networks reveal the rules of collective motion in zebrafish
When using simulated trajectories, the model recovers the ground-truth interaction rule used to generate them, as well as the number of interacting neighbours.
Benchmarking End-to-End Behavioural Cloning on Video Games
We take a step towards a general approach and study the general applicability of behavioural cloning on twelve video games, including six modern video games (published after 2010), by using human demonstrations as training data.
Playing Minecraft with Behavioural Cloning
MineRL 2019 competition challenged participants to train sample-efficient agents to play Minecraft, by using a dataset of human gameplay and a limit number of steps the environment.
A Pragmatic Look at Deep Imitation Learning
The introduction of the generative adversarial imitation learning (GAIL) algorithm has spurred the development of scalable imitation learning approaches using deep neural networks.