In machine learning for sequential decision-making, an algorithmic agent...
To facilitate research in the direction of fine-tuning foundation models...
Learning to solve long horizon temporally extended tasks with reinforcem...
We propose the Multiple View Performer (MVP) - a new architecture for 3D...
The availability of sensor-rich smart wearables and tiny, yet capable,
u...
Traditionally, learning from human demonstrations via direct behavior cl...
We held the first-ever MineRL Benchmark for Agents that Solve Almost-Lif...
Real-world tasks of interest are generally poorly defined by human-reada...
Reinforcement Learning (RL) agents can learn to solve complex sequential...
Games and simulators can be a valuable platform to execute complex
multi...
Reinforcement learning has been successful in many tasks ranging from ro...
While both navigation and manipulation are challenging topics in isolati...
While deep reinforcement learning techniques have led to agents that are...
In this paper, we present a method for learning from video demonstration...
We present a robot navigation system that uses an imitation learning
fra...
In this paper we present a technique for learning how to solve a multi-r...
While deep reinforcement learning techniques have led to agents that are...
Recent progress in AI and Reinforcement learning has shown great success...
While recent advances in deep reinforcement learning have allowed autono...