Reinforcement learning competitions advance the field by providing appropriate scope and
support to develop solutions toward a specific problem. To promote the development of …

The widespread use of experimental benchmarks in AI research has created competition
and collaboration dynamics that are still poorly understood. Here we provide an innovative …

To facilitate research in the direction of sample efficient reinforcement learning, we held the
MineRL Competition on Sample Efficient Reinforcement Learning Using Human Priors at …

Reinforcement learning competitions have formed the basis for standard research
benchmarks, galvanized advances in the state-of-the-art, and shaped the direction of the …

Although deep reinforcement learning has led to breakthroughs in many difficult domains,
these successes have required an ever-increasing number of samples, affording only a …

The task of Emotion-Cause Pair Extraction (ECPE) aims to extract all potential emotion-
cause pairs of a document without any annotation of emotion or cause clauses. Previous …

To facilitate research in the direction of sample-efficient reinforcement learning, we held the
MineRL Competition on Sample-Efficient Reinforcement Learning Using Human Priors at …

The widespread use of experimental benchmarks in AI research has created new
competition and collaboration dynamics that are still poorly understood. In this paper we …

Reinforcement learning competitions have formed the basis for standard research
benchmarks, galvanized advances in the state-of-the-art, and shaped the direction of the …

Reinforcement learning (RL) is able to solve domains without needing to learn a model of
the domain dynamics. When coupled with a neural network as a function approximator, RL …