Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning
The rapid pace of recent research in AI has been driven in part by the presence of fast and challenging simulation environments. These environments often take the form of games; with tasks ranging from simple board games, to competitive video games. We propose a new benchmark - Obstacle Tower: a high fidelity, 3D, 3rd person, procedurally generated environment. An agent playing Obstacle Tower must learn to solve both low-level control and high-level planning problems in tandem while learning from pixels and a sparse reward signal. Unlike other benchmarks such as the Arcade Learning Environment, evaluation of agent performance in Obstacle Tower is based on an agent's ability to perform well on unseen instances of the environment. In this paper we outline the environment and provide a set of baseline results produced by current state-of-the-art Deep RL methods as well as human players. These algorithms fail to produce agents capable of performing near human level.
Code (3)
Tasks
Atari GamesBoard GamesSimilar Papers 제목 키워드 기반
PPO Dash: Improving Generalization in Deep Reinforcement Learning
Deep reinforcement learning is prone to overfitting, and traditional benchmarks such as Atari 2600 benchmark can exacerbate this problem. The Obstacle Tower Challenge addresses this by using randomized environments and s…
Deep Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning
The Obstacle Tower Challenge is the task to master a procedurally generated chain of levels that subsequently get harder to complete. Whereas the most top performing entries of last year's competition used human demonstr…
Deep Reinforcement LearningReinforcement LearningTowerVision: Understanding and Improving Multilinguality in Vision-Language Models
Despite significant advances in vision-language models (VLMs), most existing work follows an English-centric design process, limiting their effectiveness in multilingual settings. In this work, we provide a comprehensive…
On the Analysis and Synthesis of Wind Turbine Side-Side Tower Load Control via Demodulation
As wind turbine power capacities continue to rise, taller and more flexible tower designs are needed for support. These designs often have the tower's natural frequency in the turbine's operating regime, increasing the r…
Prompt Learning for Oriented Power Transmission Tower Detection in High-Resolution SAR Images
Detecting transmission towers from synthetic aperture radar (SAR) images remains a challenging task due to the comparatively small size and side-looking geometry, with background clutter interference frequently hindering…
object-detectionObject DetectionPrompt Learning