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 …

[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 …

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 …

Modeling and simulating human teamwork behaviors using intelligent agents

X Fan, J Yen - Physics of life reviews, 2004‏ - Elsevier
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 …

Decentralized multi-robot cooperation with auctioned POMDPs

J Capitan, MTJ Spaan, L Merino… - … International Journal of …, 2013‏ - journals.sagepub.com
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 …

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 …

The bandit whisperer: Communication learning for restless bandits

Y Zhao, T Wang, D Nagaraj, A Taneja… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Applying Reinforcement Learning (RL) to Restless Multi-Arm Bandits (RMABs) offers a
promising avenue for addressing allocation problems with resource constraints and …

Reasoning about joint beliefs for execution-time communication decisions

M Roth, R Simmons, M Veloso - Proceedings of the fourth international …, 2005‏ - dl.acm.org
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 …

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" …