Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Castellini, Jacopo"'
Centralized training for decentralized execution paradigm emerged as the state-of-the-art approach to epsilon-optimally solving decentralized partially observable Markov decision processes. However, scalability remains a significant issue. This paper
Externí odkaz:
http://arxiv.org/abs/2408.13139
Multi-agent planning and reinforcement learning can be challenging when agents cannot see the state of the world or communicate with each other due to communication costs, latency, or noise. Partially Observable Stochastic Games (POSGs) provide a mat
Externí odkaz:
http://arxiv.org/abs/2311.09459
Publikováno v:
Neural Comput & Applic (2022)
Policy gradient methods have become one of the most popular classes of algorithms for multi-agent reinforcement learning. A key challenge, however, that is not addressed by many of these methods is multi-agent credit assignment: assessing an agent's
Externí odkaz:
http://arxiv.org/abs/2012.11258
Autor:
Castellini, Jacopo
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. Neural Turing Machines (NTMs) attempt to mitigate this issue by providing th
Externí odkaz:
http://arxiv.org/abs/1904.02478
Autor:
Castellini, Jacopo
Publikováno v:
Numerical Algorithms 74(2), 561-571, Springer, 2017
In this work, we are presenting an efficient way to compute the geometric mean of two positive definite matrices times a vector. For this purpose, we are inspecting the application of methods based on Krylov spaces to compute the square root of a mat
Externí odkaz:
http://arxiv.org/abs/1903.01189
Analysing Factorizations of Action-Value Networks for Cooperative Multi-Agent Reinforcement Learning
Publikováno v:
Auton Agent Multi-Agent Syst 35, 25 (2021)
Recent years have seen the application of deep reinforcement learning techniques to cooperative multi-agent systems, with great empirical success. However, given the lack of theoretical insight, it remains unclear what the employed neural networks ar
Externí odkaz:
http://arxiv.org/abs/1902.07497
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Castellini, Jacopo
Multi-agent systems [33, 136] are an ubiquitous presence in our everyday life: our entire society could be seen as a huge multi-agent system in which each individual has to perform in an environment populated by other entities, each motivated by its
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3d410d16f1f16c7c286eb100242b7c3
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.