activity
20102024
most citedA Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

2.1k citations · 9.2k across the 77 of their papers we have counts for

collaborators
Showing 2016 · cs.AIShow all

2 papers · 2 filters

cs.AI2016★ 1.1k cited

Learning to Communicate with Deep Multi-Agent Reinforcement Learning

Jakob N. Foerster, Yannis M. Assael, Nando de Freitas +1

We consider the problem of multiple agents sensing and acting in environments with the goal of maximising their shared utility. In these environments, agents must learn communicati…

cs.AI2016★ 80 cited

Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks

Jakob N. Foerster, Yannis M. Assael, Nando de Freitas +1

We propose deep distributed recurrent Q-networks (DDRQN), which enable teams of agents to learn to solve communication-based coordination tasks. In these tasks, the agents are not…