Do you have experience in multiagent reinforcement learning, game theory and/or other forms of interactive learning? Then have a look at this vacancy and contact me!
Month: November 2020
NeurIPS camready: MDP Homomorphic Networks
In this work we show how symmetries that can occur in MDPs can be exploited for more efficient deep reinforcement learning.
NeurIPS Camready: Multi-agent active perception with prediction rewards
This paper shows that also in decentralized multiagent settings we can employ “prediction rewards” for active perception. (Intuitively leading to a type of voting that we try to optimize).
NeurIPS Camready: Influence-Augmented Online Planning
The camready version of Influence-Augmented Online Planning for Complex Environments is now available.
In this work, we show that by learning approximate representations of influence, we can speed up online planning (POMCP) sufficiently to get better performance when the time for online decision making is constrained.