1k citations · 4.2k across the 34 of their papers we have counts for
3 papers · 2 filters
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
Maruan Al-Shedivat, Trapit Bansal, Yuri Burda +3
Ability to continuously learn and adapt from limited experience in nonstationary environments is an important milestone on the path towards general intelligence. In this paper, we…
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Ryan Lowe, Yi Wu, Aviv Tamar +3
We explore deep reinforcement learning methods for multi-agent domains. We begin by analyzing the difficulty of traditional algorithms in the multi-agent case: Q-learning is challe…
Prediction and Control with Temporal Segment Models
Nikhil Mishra, Pieter Abbeel, Igor Mordatch
We introduce a method for learning the dynamics of complex nonlinear systems based on deep generative models over temporal segments of states and actions. Unlike dynamics models th…