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Found 5 papers, 2 papers with code
Reward-Respecting Subtasks for Model-Based Reinforcement Learning
Each subtask is solved to produce an option, and then a model of the option is learned and made available to the planning process.
Model-based Reinforcement Learning
reinforcement-learning
+2
When should agents explore?
Exploration remains a central challenge for reinforcement learning (RL).
Adapting Behaviour for Learning Progress
Determining what experience to generate to best facilitate learning (i. e. exploration) is one of the distinguishing features and open challenges in reinforcement learning.
Grounded Language Learning in a Simulated 3D World
Trained via a combination of reinforcement and unsupervised learning, and beginning with minimal prior knowledge, the agent learns to relate linguistic symbols to emergent perceptual representations of its physical surroundings and to pertinent sequences of actions.
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models
We present a framework for efficient inference in structured image models that explicitly reason about objects.
