Search Results for author: Jacopo Castellini

Found 2 papers, 0 papers with code

Difference Rewards Policy Gradients

no code implementations21 Dec 2020 Jacopo Castellini, Sam Devlin, Frans A. Oliehoek, Rahul Savani

Policy gradient methods have become one of the most popular classes of algorithms for multi-agent reinforcement learning.

counterfactual Multi-agent Reinforcement Learning +2

Learning Numeracy: Binary Arithmetic with Neural Turing Machines

no code implementations4 Apr 2019 Jacopo Castellini

One of the main problems encountered so far with recurrent neural networks is that they struggle to retain long-time information dependencies in their recurrent connections.

Cannot find the paper you are looking for? You can Submit a new open access paper.