Results 51 to 60 of about 58,229 (203)
, 2021 Our future is that of a mixed society of people and AI artifacts. A multitude of devices in our homes will need not only to make intelligent decisions, but they will also need to coordinate with each other to serve us well. Cars will have to coordinate to allow safe road crossings, avoiding accidents.
Osman, Nardine +13 more
openaire +1 more source
Context Awareness and Human–Robot Interaction Optimization for Museum Intelligent Guide Robot
Advanced Intelligent Systems, EarlyView.This study presents a context‐aware human–robot interaction framework designed for intelligent museum guide robots. The system features a three‐layer architecture—perception, understanding, and behavior execution—that enables adaptive and meaningful interactions with museum visitors.
Anna Zou, Yue Meng, Shijing Tong
wiley +1 more source
Computers and Education: Artificial IntelligenceThe rapid adoption of Large Language Models (LLMs) such as GPT-4 and DeepSeek R1 is transforming learning in higher education, yet unstructured use can weaken critical thinking by encouraging cognitive offloading, metacognitive disengagement, and reduced
Mireia Vendrell, Samantha-Kaye Johnston
doaj +1 more source
Anonymity and Information Hiding in Multiagent Systems [PDF]
, 2003 We provide a framework for reasoning about information-hiding requirements in multiagent systems and for reasoning about anonymity in particular. Our framework employs the modal logic of knowledge within the context of the runs and systems framework ...
Halpern, Joseph Y., O'Neill, Kevin R.
core +6 more sources
, 2011 The goal of this research is to develop agents that are adaptive and predictable and timely. At first blush, these three requirements seem contradictory.
Gordon, D. F.
core +1 more source
Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs
Advanced Intelligent Systems, EarlyView.This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza +2 more
wiley +1 more source
Consensus of Discrete Time Second-Order Multiagent Systems with Time Delay
Discrete Dynamics in Nature and Society, 2012 The consensus problem for discrete time second-order multiagent systems with time delay is studied. Some effective methods are presented to deal with consensus problems in discrete time multiagent systems.
Wei Zhu
doaj +1 more source
Stability Analysis of State Delay Multiagent Systems with Observer-Based Control Protocols
Journal of Mathematics, 2023 The consistency problem of multiagent systems with the output feedback and state delay was considered in this paper. First, the reduced-order observer based on the consensus protocol of state delay is designed, and the consensus protocol is proposed by ...
Xingmei Li +3 more
doaj +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
Advanced Intelligent Systems, EarlyView.This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Multiagent Consensus Control under Network-Induced Constraints
Journal of Applied Mathematics, 2013 Mean consensus problem is studied using a class of discrete time multiagent systems in which information exchange is subjected to some network-induced constraints. These constraints include package dropout, time delay, and package disorder.
Won Il Kim +3 more
doaj +1 more source