Takes from Agence, an interactive VR project
Simulation

RL Agents: SOS!

A new multimedia experience lets audience members help artificially intelligent creatures work together to survive. Agence, an interactive virtual reality (VR) project blends audience participation with reinforcement learning to create an experience that’s half film, half video game.
2 min read
Map of the area analyzed in Cascadia and sketch of the subduction zone
Simulation

Prelude to a Quake?

Geologists call them slow slips: deep, low-frequency earthquakes that can last a month but have little effect on the surface. A model trained to predict such events could help with forecasting potentially catastrophic quakes.
1 min read
Different chess moves
Simulation

Chess: The Next Move

AI has humbled human chess masters. Now it’s helping them take the game to the next level. DeepMind and retired chess champion Vladimir Kramnik trained AlphaZero, a reinforcement learning model that bested human experts in chess, Go, and Shogi, to play-test changes in the rules.
1 min read
Tennis simulator Vid2Player working
Simulation

Wimbledon in a Box

Covid shut down the tennis tournament at Wimbledon this year, but a new model simulates showdowns between the sport’s greatest players. Stanford researchers developed Vid2Player, a system that simulates the footwork, positioning, and strokes of tennis pros like Roger Federer.
1 min read
Sequence of an autonomous fighter pilot
Simulation

AI Versus Ace

An autonomous fighter pilot shot down a human aerial ace in virtual combat. Built by defense contractor Heron Systems, the system also defeated automated rivals from seven other companies to win the AlphaDogfight trial.
2 min read
Dozens of drones coordinating movements
Simulation

Drones of a Feather

Deep learning is coordinating drones so they can flock together without colliding. Caltech researchers Soon-Jo Chung and Yisong Yue developed a pair of models that enables swarms of networked drones to navigate autonomously through cluttered environments.
1 min read
Information related to Policy Adaptation during Deployment (Pad)
Simulation

Same Job, Different Scenery

People who take driving lessons during daytime don’t need instruction in driving at night. They recognize that the difference doesn’t disturb their knowledge of how to drive. Similarly, a new reinforcement learning method manages superficial variations in the environment without re-training.
2 min read
Data related to a new reinforcement learning approach
Simulation

Eyes on the Prize

When the chips are down, humans can track critical details without being distracted by irrelevancies. New research helps reinforcement learning models similarly focus on the most important details.
2 min read
Takes from videogame Source of Madness
Simulation

Monsters in Motion

How do you control a video game that generates a host of unique monsters for every match? With machine learning, naturally. The otherworldly creatures in Source of Madness learn how to target players through reinforcement learning.
1 min read
Graphs and data related to Plan2Vec
Simulation

Visual Strategies for RL

Reinforcement learning can beat humans at video games, but humans are better at coming up with strategies to master more complex tasks. New work enables neural networks to connect the dots.
2 min read
Results of a technique that interprets reflected light to reveal objects outside the line of sight
Simulation

Periscope Vision

Wouldn’t it be great to see around corners? Deep learning researchers are working on it. Researchers developed deep-inverse correlography, a technique that interprets reflected light to reveal objects outside the line of sight.
2 min read
Anima Anandkumar
Simulation

Anima Anandkumar: The Power of Simulation

We’ve had great success with supervised deep learning on labeled data. Now it’s time to explore other ways to learn: training on unlabeled data, lifelong learning, and especially letting models explore a simulated environment before transferring what they learn to the real world.
2 min read
Illustration of a crystal snowball
Simulation

Simulation Substitutes for Data

The future of machine learning may depend less on amassing ground-truth data than simulating the environment in which a model will operate. Deep learning works like magic with enough high-quality data. When examples are scarce, though, researchers are using simulation to fill the gap.
1 min read
Information related to Implicit Reinforcement without Interaction at Scale (IRIS)
Simulation

Different Skills From Different Demos

Reinforcement learning trains models by trial and error. In batch reinforcement learning (BRL), models learn by observing many demonstrations by a variety of actors. But what if one doctor is handier with a scalpel while another excels at suturing?
2 min read
Observational dropout
Simulation

Seeing the World Blindfolded

In reinforcement learning, if researchers want an agent to have an internal representation of its environment, they’ll build and train a world model that it can refer to. New research shows that world models can emerge from standard training, rather than needing to be built separately.
2 min read

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