NGI Explorers Program is looking for Europe's Top researchers and innovators in emerging Internet technologies to join a unique opportunity in the US.
3-6 MONTH EXPEDITION TO THE US
Work directly with a US partner to accelerate your idea.
100% SPONSORSHIP PLAN
Financial support will be 100% sponsored with EU public grants.
A coach will give direct support throughout the expedition.
- Decision-making in partially observable Markov Decision Processes.
- Satisfying probabilistic guarantees on the behavior of a learned agent when approximate value functions (i.e. neural networks) are used to measure utility.
- Control of hybrid systems resulting from the discretization of continuous space induced by a given set of behavioral specifications. Such specifications are typically defined by a temporal logic such as computation tree logic and linear temporal logic.
- Decision-making in adversarial stochastic games.
- Reinforcement learning as a constrained optimization problem wherein expected long-term rewards are to be maximized while satisfying bounds on the probabilities of satisfying various behavioral specifications.
A basic understanding of Reinforcement Learning.
Source: NGI Explorers Program
Illustration Photo: SISYPHUS is a robot that learns to crawl using a simple AI algorithm called reinforcement learning. The robot tries random actions at first and learns if it is moving forward or backward. Over time it connects actions that move it forward. (credits: mangtronix / Flickr Creative Commons Attribution-ShareAlike 2.0 Generic (CC BY-SA 2.0))