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Decentralized control of partially observable Markov decision processes
C Amato, G Chowdhary, A Geramifard… - … IEEE Conference on …, 2013 - ieeexplore.ieee.org
Markov decision processes (MDPs) are often used to model sequential decision problems
involving uncertainty under the assumption of centralized control. However, many large …
involving uncertainty under the assumption of centralized control. However, many large …
[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 …
cooperative systems. It is aimed at graduate students and researchers in the fields of …
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 …
because it treats uncertainty in sensing and acting in a principled way. In single-agent …
Modeling and simulating human teamwork behaviors using intelligent agents
Among researchers in multi-agent systems there has been growing interest in using
intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is …
intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is …
Decentralized multi-robot cooperation with auctioned POMDPs
Planning under uncertainty faces a scalability problem when considering multi-robot teams,
as the information space scales exponentially with the number of robots. To address this …
as the information space scales exponentially with the number of robots. To address this …
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 …
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 …
modeled as DEC-POMDPs. The algorithm helps overcome the high computational …
The bandit whisperer: Communication learning for restless bandits
Applying Reinforcement Learning (RL) to Restless Multi-Arm Bandits (RMABs) offers a
promising avenue for addressing allocation problems with resource constraints and …
promising avenue for addressing allocation problems with resource constraints and …
Reasoning about joint beliefs for execution-time communication decisions
Just as POMDPs have been used to reason explicitly about uncertainty in single-agent
systems, there has been recent interest in using multi-agent POMDPs to coordinate teams of …
systems, there has been recent interest in using multi-agent POMDPs to coordinate teams of …
Extending RDBMSs to support sparse datasets using an interpreted attribute storage format
JL Beckmann, A Halverson… - … Conference on Data …, 2006 - ieeexplore.ieee.org
" Sparse" data, in which relations have many attributes that are null for most tuples, presents
a challenge for relational database management systems. If one uses the normal" …
a challenge for relational database management systems. If one uses the normal" …