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In many practical applications, decision-making processes must balance the costs of acquiring information with the benefits it provides. Traditional control systems often assume full observability, an unrealistic assumption when…

人工智能 · 计算机科学 2025-01-24 Taiyi Wang , Jianheng Liu , Bryan Lee , Zhihao Wu , Yu Wu

The intent of this research is to generate a set of non-dominated policies from which one of two agents (the leader) can select a most preferred policy to control a dynamic system that is also affected by the control decisions of the other…

最优化与控制 · 数学 2014-04-18 Yanling Chang , Alan L. Erera , Chelsea C. White

We consider a distributionally robust Partially Observable Markov Decision Process (DR-POMDP), where the distribution of the transition-observation probabilities is unknown at the beginning of each decision period, but their realizations…

最优化与控制 · 数学 2020-12-09 Hideaki Nakao , Ruiwei Jiang , Siqian Shen

The recently announced Super Wi-Fi Network proposal in United States is aiming to enable Internet access in a nation-wide area. As traditional cable-connected power supply system becomes impractical or costly for a wide range wireless…

信息论 · 计算机科学 2020-08-05 Tingwu Wang , Jian Wang , Chunxiao Jiang , Jingjing Wang , Yong Ren

Cell-free massive multi-input multi-output (CFmMIMO) offers uniform service quality through distributed access points (APs), yet unresolved issues remain. This paper proposes a heterogeneous system design that goes beyond the original…

信息论 · 计算机科学 2024-08-16 Wei Jiang , Hans D. Schotten

This work addresses the challenge of a robot using real-time feedback from contact sensors to reliably manipulate a movable object on a cluttered tabletop. We formulate contact manipulation as a partially observable Markov decision process…

机器人学 · 计算机科学 2016-05-03 Michael C. Koval , David Hsu , Nancy S. Pollard , Siddhartha S. Srinivasa

We consider the problem of interactive partially observable Markov decision processes (I-POMDPs), where the agents are located at the nodes of a communication network. Specifically, we assume a certain message type for all messages.…

人工智能 · 计算机科学 2020-11-11 Yitao Chen , Deepanshu Vasal

Partially Observable Markov Decision Processes (POMDPs) are a natural and general model in reinforcement learning that take into account the agent's uncertainty about its current state. In the literature on POMDPs, it is customary to assume…

机器学习 · 计算机科学 2022-03-24 Noah Golowich , Ankur Moitra , Dhruv Rohatgi

The decoupling of data and control planes, as proposed for 5G networks, will enable the efficient implementation of multitier networks where user equipment (UE) nodes obtain coverage and connectivity through the top-tier macro-cells, and,…

Partially observable Markov decision processes (POMDPs) provide a modeling framework for a variety of sequential decision making under uncertainty scenarios in artificial intelligence (AI). Since the states are not directly observable in a…

系统与控制 · 计算机科学 2019-05-21 Mohamadreza Ahmadi , Nils Jansen , Bo Wu , Ufuk Topcu

Decision making under uncertainty is at the heart of any autonomous system acting with imperfect information. The cost of solving the decision making problem is exponential in the action and observation spaces, thus rendering it unfeasible…

人工智能 · 计算机科学 2024-06-18 Tom Yotam , Vadim Indelman

Recent years have seen human robot collaboration (HRC) quickly emerged as a hot research area at the intersection of control, robotics, and psychology. While most of the existing work in HRC focused on either low-level human-aware motion…

人机交互 · 计算机科学 2018-04-02 Wei Zheng , Bo Wu , Hai Lin

This paper investigates a cell-free massive multiple-input-multiple-output (CF-mMIMO) integrated sensing and communication (ISAC) system that addresses the critical challenge of information leakage to potential eavesdroppers located within…

信号处理 · 电气工程与系统科学 2026-03-20 Ruiguang Wang , Takumi Takahashi , Hideki Ochiai

Many current large-scale multiagent team implementations can be characterized as following the belief-desire-intention (BDI) paradigm, with explicit representation of team plans. Despite their promise, current BDI team approaches lack tools…

多智能体系统 · 计算机科学 2011-09-13 R. Nair , M. Tambe

We present an alternative view for the study of optimal control of partially observed Markov Decision Processes (POMDPs). We first revisit the traditional (and by now standard) separated-design method of reducing the problem to fully…

最优化与控制 · 数学 2024-12-20 Serdar Yüksel

User-centric cell-free (UCCF) massive multiple-input multiple-output (MIMO) systems are considered a viable solution to realize the advantages offered by cell-free (CF) networks, including reduced interference and consistent quality of…

信息论 · 计算机科学 2025-04-15 S. Salehi , S. Mashdour , O. Tamyigit , S. Seyedmasoumian , M. Moradikia , R. C. de Lamare , A. Schmeink

Cell-Free Massive MIMO (CF mMIMO) has emerged as a potential enabler for future networks. It has been shown that these networks are much more energy-efficient than classical cellular systems when they are serving users at peak capacity.…

信号处理 · 电气工程与系统科学 2024-04-30 Robbert Beerten , Vida Ranjbar , Andrea P. Guevara , Hazem Sallouha , Sofie Pollin

In this paper, we consider a queue-aware distributive resource control algorithm for two-hop MIMO cooperative systems. We shall illustrate that relay buffering is an effective way to reduce the intrinsic half-duplex penalty in cooperative…

机器学习 · 计算机科学 2015-05-20 Rui Wang , Vincent K. N. Lau , Ying Cui

We consider partially observable Markov decision processes (POMDPs) with a set of target states and positive integer costs associated with every transition. The traditional optimization objective (stochastic shortest path) asks to minimize…

人工智能 · 计算机科学 2016-05-12 Tomáš Brázdil , Krishnendu Chatterjee , Martin Chmelík , Anchit Gupta , Petr Novotný

We address the problem of controlling a mobile robot to explore a partially known environment. The robot's objective is the maximization of the amount of information collected about the environment. We formulate the problem as a partially…

机器人学 · 计算机科学 2017-03-08 Mikko Lauri , Risto Ritala