Imitation Learning
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Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning
The key technical challenge is that the symbol grounding is prone to error with limited training data and leads to subsequent symbolic planning failures.
Learning Vision-based Flight in Drone Swarms by Imitation
Decentralized drone swarms deployed today either rely on sharing of positions among agents or detecting swarm members with the help of visual markers.
IMITATION LEARNING MOTION CAPTURE UNSUPERVISED DOMAIN ADAPTATION
Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging Agents
We present here a method for training a robot for backchannel generation during a human-robot interaction within the reinforcement learning (RL) framework, with the goal of maintaining high engagement level.
Combining learned skills and reinforcement learning for robotic manipulations
We show successful learning of policies for composite manipulation tasks such as making a simple breakfast.
Non-Monotonic Sequential Text Generation
Standard sequential generation methods assume a pre-specified generation order, such as text generation methods which generate words from left to right.
Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation
Visual paragraph generation aims to automatically describe a given image from different perspectives and organize sentences in a coherent way.
Self-Imitation Learning of Locomotion Movements through Termination Curriculum
In this paper, we propose and evaluate a novel combination of techniques for accelerating the learning of stable locomotion movements through self-imitation learning of synthetic animations.
Deep Reinforcement Learning for Personalized Search Story Recommendation
In recent years, \emph{search story}, a combined display with other organic channels, has become a major source of user traffic on platforms such as e-commerce search platforms, news feed platforms and web and image search platforms.
Learning Goal-Oriented Visual Dialog Agents: Imitating and Surpassing Analytic Experts
This paper tackles the problem of learning a questioner in the goal-oriented visual dialog task.
Efficient Exploration with Self-Imitation Learning via Trajectory-Conditioned Policy
This paper proposes a method for learning a trajectory-conditioned policy to imitate diverse demonstrations from the agent's own past experiences.
EFFICIENT EXPLORATION IMITATION LEARNING MONTEZUMA'S REVENGE