[کتاب][B] A concise introduction to decentralized POMDPs

FA Oliehoek, C Amato - 2016‏ - Springer
This book presents an overview of formal decision making methods for decentralized
cooperative systems. It is aimed at graduate students and researchers in the fields of …

Multi-agent reinforcement learning as a rehearsal for decentralized planning

L Kraemer, B Banerjee - Neurocomputing, 2016‏ - Elsevier
Decentralized partially observable Markov decision processes (Dec-POMDPs) are a
powerful tool for modeling multi-agent planning and decision-making under uncertainty …

Decision making in multiagent systems: A survey

Y Rizk, M Awad, EW Tunstel - IEEE Transactions on Cognitive …, 2018‏ - ieeexplore.ieee.org
Intelligent transport systems, efficient electric grids, and sensor networks for data collection
and analysis are some examples of the multiagent systems (MAS) that cooperate to achieve …

Optimal and approximate Q-value functions for decentralized POMDPs

FA Oliehoek, MTJ Spaan, N Vlassis - Journal of Artificial Intelligence …, 2008‏ - jair.org
Decision-theoretic planning is a popular approach to sequential decision making problems,
because it treats uncertainty in sensing and acting in a principled way. In single-agent …

Formal models and algorithms for decentralized decision making under uncertainty

S Seuken, S Zilberstein - Autonomous Agents and Multi-Agent Systems, 2008‏ - Springer
Over the last 5 years, the AI community has shown considerable interest in decentralized
control of multiple decision makers or “agents” under uncertainty. This problem arises in …

Decentralized pomdps

FA Oliehoek - Reinforcement learning: state-of-the-art, 2012‏ - Springer
This chapter presents an overview of the decentralized POMDP (Dec-POMDP) framework. In
a Dec-POMDP, a team of agents collaborates to maximize a global reward based on local …

Online planning for multi-agent systems with bounded communication

F Wu, S Zilberstein, X Chen - Artificial Intelligence, 2011‏ - Elsevier
We propose an online algorithm for planning under uncertainty in multi-agent settings
modeled as DEC-POMDPs. The algorithm helps overcome the high computational …

[PDF][PDF] Memory-Bounded Dynamic Programming for DEC-POMDPs.

S Seuken, S Zilberstein - IJCAI, 2007‏ - ijcai.org
Decentralized decision making under uncertainty has been shown to be intractable when
each agent has different partial information about the domain. Thus, improving the …

Improved memory-bounded dynamic programming for decentralized POMDPs

S Seuken, S Zilberstein - arxiv preprint arxiv:1206.5295, 2012‏ - arxiv.org
Memory-Bounded Dynamic Programming (MBDP) has proved extremely effective in solving
decentralized POMDPs with large horizons. We generalize the algorithm and improve its …

Policy iteration for decentralized control of Markov decision processes

DS Bernstein, C Amato, EA Hansen… - Journal of Artificial …, 2009‏ - jair.org
Coordination of distributed agents is required for problems arising in many areas, including
multi-robot systems, networking and e-commerce. As a formal framework for such problems …