Three major challenges in reinforcement learning are the complex dynamic...
Multitask learning is a powerful framework that enables one to simultane...
In Causal Bayesian Optimization (CBO), an agent intervenes on an unknown...
We consider the interaction among agents engaging in a driving task and ...
Contextual Bayesian optimization (CBO) is a powerful framework for seque...
We consider model-based multi-agent reinforcement learning, where the
en...
We formulate the novel class of contextual games, a type of repeated gam...
We consider a repeated sequential game between a learner, who plays firs...
We consider robust optimization problems, where the goal is to optimize ...
We study a general class of repeated auctions, such as the ones found in...
We consider the problem of learning to play a repeated multi-agent game ...
Games with continuous strategy sets arise in several machine learning
pr...
This paper investigates reverse auctions that involve continuous values ...
This paper investigates reverse auctions that involve continuous values ...