Search Results - Computing methodologies Artificial intelligence Distributed artificial intelligence

Software Engineering Using Autonomous Agents: Are We There Yet? by Suri, Samdyuti, Das, Sankar Narayan, Singi, Kapil, Dey, Kuntal, Sharma, Vibhu Saujanya, Kaulgud, Vikrant

“…Autonomous agents equipped with Large Language Models (LLMs) are rapidly gaining prominence as a revolutionary technology within the realm of Software…”
Get full text

Social Momentum: A Framework for Legible Navigation in Dynamic Multi-Agent Environments by Mavrogiannis, Christoforos I., Thomason, Wil B., Knepper, Ross A.

“…Intent-expressive robot motion has been shown to result in increased efficiency and reduced planning efforts for copresent humans. Existing frameworks for…”
Get full text

FedLight: Federated Reinforcement Learning for Autonomous Multi-Intersection Traffic Signal Control by Ye, Yutong, Zhao, Wupan, Wei, Tongquan, Hu, Shiyan, Chen, Mingsong

“…Although Reinforcement Learning (RL) has been successfully applied in traffic control, it suffers from the problems of high average vehicle travel time and…”
Get full text

Automated Design of Complex Analog Circuits with Multiagent based Reinforcement Learning by Zhang, Jinxin, Bao, Jiarui, Huang, Zhangcheng, Zeng, Xuan, Lu, Ye

“…Despite the effort of analog circuit design automation, currently complex analog circuit design still requires extensive manual iterations, making it labor…”
Get full text

Invited: Towards Fully Intelligent Transportation through Infrastructure-Vehicle Cooperative Autonomous Driving: Challenges and Opportunities by Liu, Shaoshan, Yu, Bo, Tang, Jie, Zhu, Qi

“…The infrastructure-vehicle cooperative autonomous driving approach relies on the cooperation between intelligent roads and intelligent vehicles. This approach…”
Get full text

A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning by Fu, Yonggan, Zhang, Yongan, Li, Chaojian, Yu, Zhongzhi, Lin, Yingyan

“…Driven by the explosive interest in applying deep reinforcement learning (DRL) agents to numerous real-time control and decision-making applications, there has…”
Get full text

Perspective Multi-Player Games by Kupferman, Orna, Shenwald, Noam

“…Perspective games model multi-agent systems in which agents can view only the parts of the system that they own. Unlike the observation-based model of partial…”
Get full text

FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers by Chai, Zheng, Chen, Yujing, Anwar, Ali, Zhao, Liang, Cheng, Yue, Rangwala, Huzefa

“…Federated learning (FL) involves training a model over massive distributed devices, while keeping the training data localized and private…”
Get full text

Accelerating Distributed Reinforcement learning with In-Switch Computing by Li, Youjie, Liu, Iou-Jen, Yuan, Yifan, Chen, Deming, Schwing, Alexander, Huang, Jian

“… Unlike distributed deep neural network (DNN) training, the distributed RL training has its unique workload characteristics - it generates orders of magnitude more iterations with much smaller sized but more frequent gradient aggregations…”
Get full text

Social Influence Diffusion and Coordinated Decision Making on Networks by Stirling, Wynn C., Tummolini, Luca

“…Essential properties of a social influence network are a) the mechanism by which social influence is diffused throughout the network and b) the mechanism by…”
Get full text

Increasing Coverage of Information Diffusion Processes by Reducing the Number of Initial Seeds by Jankowski, Jarosław, Michalski, Radosław, Bródka, Piotr, Karczmarczyk, Artur

“…Initialization of information spreading processes within complex networks is usually based on selection of initial nodes as a seed set. While most methods are…”
Get full text

MMDFL: Multi-Model-based Decentralized Federated Learning for Resource-Constrained AIoT Systems by Yan, Dengke, Yang, Yanxin, Hu, Ming, Fu, Xin, Chen, Mingsong

“…Along with the prosperity of Artificial Intelligence (AI) techniques, more and more Artificial Intelligence of Things (AIoT…”
Get full text

Knowledge Aggregation with Subjective Logic in Multi-Agent Self-Adaptive Cyber-Physical Systems by Petrovska, Ana, Quijano, Sergio, Gerostathopoulos, Ilias, Pretschner, Alexander

“…Modern software systems, such as cyber-physical systems (CPSs), operate in complex and dynamic environments. With the continuous and unanticipated change in…”
Get full text

Mimicking Associative Learning of Rats via a Neuromorphic Robot in Open Field Maze Using Spatial Cell Models by Liu, Tianze, Bakr Siddique, Md Abu, An, Hongyu

“…Data-driven Artificial Intelligence (AI) approaches have exhibited remarkable prowess across various cognitive tasks using extensive training data…”
Get full text

Towards Autonomous Testing Agents via Conversational Large Language Models by Feldt, Robert, Kang, Sungmin, Yoon, Juyeon, Yoo, Shin

“…Software testing is an important part of the development cycle, yet it requires specialized expertise and substantial developer effort to adequately test…”
Get full text

A coordination mechanism to replicate large-scale multi-agent systems by Ductor, Sylvain, Guessoum, Zahia

“…Distributed cooperative applications are now increasingly designed as Multi-Agent Systems (MAS…”
Get full text

Are We Trusting AI Too Much?: Examining Human-Robot Interactions in the Real World by Howard, Ayanna

“…Intelligent systems, especially those with an embodied construct, are becoming pervasive in our society. From chatbots to rehabilitation robotics, from…”
Get full text

Research challenges of autonomic computing by Kephart, Jeffrey O.

“…Autonomic computing is a grand-challenge vision of the future in which computing systems will manage themselves in accordance with high-level objectives specified by humans…”
Get full text

Trust-Region Method with Deep Reinforcement Learning in Analog Design Space Exploration by Yang, Kai-En, Tsai, Chia-Yu, Shen, Hung-Hao, Chiang, Chen-Feng, Tsai, Feng-Ming, Wang, Chung-An, Ting, Yiju, Yeh, Chia-Shun, Lai, Chin-Tang

“…This paper introduces new perspectives on analog design space search. To minimize the time-to-market, this endeavor better cast as constraint satisfaction…”
Get full text

Flexible Modelling using Conversational Agents by Perez-Soler, Sara, Guerra, Esther, de Lara, Juan

“…The advances in natural language processing and the wide use of social networks have boosted the proliferation of chatbots. These are software services…”
Get full text