Artificial Intelligence Development Races in Heterogeneous Settings
Teesside University（提赛德大学）；Universidade Nova de Lisboa（里斯本新大学）；Universidade de Lisboa（里斯本大学）；Université Libre de Bruxelles（布鲁塞尔自由大学）；Vrije Universiteit Brussel（布鲁塞尔自由大学）；UC Berkeley（加州大学伯克利分校）；Université Libre de Bruxelles-Vrije Universiteit Brussel（布鲁塞尔自由大学-布鲁塞尔自由大学）
Theodor Cimpeanu, Francisco C. Santos, Luis Moniz Pereira, Tom Lenaerts, The Anh Han
备注：
42 pages, 13 figures, accepted for publication in Nature Scientific Reports
Regulation of advanced technologies such as Artificial Intelligence (AI) has become increasingly important, given the associated risks and apparent ethical issues. With the great benefits promised from being able to first supply such technologies, safety precautions and societal consequences might be ignored or shortchanged in exchange for speeding up the development, therefore engendering a racing narrative among the developers. Starting from a game-theoretical model describing an idealised technology race in a fully connected world of players, here we investigate how different interaction structures among race participants can alter collective choices and requirements for regulatory actions. Our findings indicate that, when participants portray a strong diversity in terms of connections and peer-influence (e.g., when scale-free networks shape interactions among parties), the conflicts that exist in homogeneous settings are significantly reduced, thereby lessening the need for regulatory actions. Furthermore, our results suggest that technology governance and regulation may profit from the world's patent heterogeneity and inequality among firms and nations, so as to enable the design and implementation of meticulous interventions on a minority of participants, which is capable of influencing an entire population towards an ethical and sustainable use of advanced technologies.
RACER: Rational Artificial Intelligence Car-following-model Enhanced by Reality
Department of Civil Engineering（土木工程系）；Department of Aerospace Engineering（航空航天工程系）；Department of Civil, Environmental, and Geo-Engineering（土木、环境与地球工程系）
Robotics is the next frontier in the progress of Artificial Intelligence (AI), as the real world in which robots operate represents an enormous, complex, continuous state space with inherent real-time requirements. One extreme challenge in robotics is currently formed by autonomous drone racing. Human drone racers can fly through complex tracks at speeds of up to 190 km/h. Achieving similar speeds with autonomous drones signifies tackling fundamental problems in AI under extreme restrictions in terms of resources. In this article, we present the winning solution of the first AI Robotic Racing …
Zhejiang University（浙江大学）；Zhejiang Wanfeng Technology Development Company Limited（浙江万丰科技开发有限公司）
Collective intelligence is manifested when multiple agents coherently work in observation, interaction, decision-making and action. In this paper, we define and quantify the intelligence level of heterogeneous agents group with the improved Anytime Universal Intelligence Test(AUIT), based on an extension of the existing evaluation of homogeneous agents group. The relationship of intelligence level with agents composition, group size, spatial complexity and testing time is analyzed. The intelligence level of heterogeneous agents groups is compared with the homogeneous ones to analyze the effect…
Teesside University（提赛德大学）；NOVA Laboratory for Computer Science and Informatics (NOVA LINCS)（NOVA计算机科学与信息学实验室（NOVA LINCS））；Universidade Nova de Lisboa（里斯本新大学）；Université Libre de Bruxelles（布鲁塞尔自由大学（法语区））；Vrije Universiteit Brussel（布鲁塞尔自由大学（荷语区））；INESC-ID（系统与计算机工程、科学与发展研究所）；Instituto Superior Tecnico（高等技术学院）；Universidade de Lisboa（里斯本大学）
The field of Artificial Intelligence (AI) is going through a period of great expectations, introducing a certain level of anxiety in research, business and also policy. This anxiety is further energised by an AI race narrative that makes people believe they might be missing out. Whether real or not, a belief in this narrative may be detrimental as some stake-holders will feel obliged to cut corners on safety precautions, or ignore societal consequences just to "win". Starting from a baseline model that describes a broad class of technology races where winners draw a significant benefit compare…
Prospects for Using Artificial Intelligence to Understand Intrinsic Kinetics of Heterogeneous Catalytic Reactions
organization= School of Chemical \& Biomolecular Engineering, Georgia Institute of Technology , addressline= 311 Ferst Drive NW , city= Atlanta , postcode= 30332 , state= GA , country= USA；organization= Department of Chemical Engineering, Carnegie Mellon University , addressline= 5000 Forbes Street , city= Pittsburgh , postcode= 15213 , state= PA , country= USA
Heterogeneous Robot Collaboration in Unstructured Environments with Grounded Generative Intelligence
Dept. of Electrical and Computer Engineering at Texas A&M University（德克萨斯A&M大学电气与计算机工程系）；GRASP Laboratory at the University of Pennsylvania（宾夕法尼亚大学GRASP实验室）
Strategic Insights from Simulation Gaming of AI Race Dynamics
Wichita State University（威奇托州立大学）；Barton School of Business（巴顿商学院）；Transformative Futures Institute（变革性未来研究所）；University of Cambridge（剑桥大学）；Centre for the Study of Existential Risk（存在风险研究中心）；Centre for the Future of Intelligence（未来智能中心）；Oxford University（牛津大学）；London Initiative for Safe AI（伦敦安全人工智能倡议）；Monash University（莫纳什大学）；Monash Sustainable Development Institute（莫纳什可持续发展研究所）；BehaviourWorks Australia（澳大利亚行为研究中心）
MOD-X: A Modular Open Decentralized eXchange Framework proposal for Heterogeneous Interoperable Artificial Intelligence Agents
James Silberrad Brown Center for Artificial Intelligence（詹姆斯·西伯拉德·布朗人工智能中心）；Carnegie Mellon University（卡内基梅隆大学）；Amazon GenAI（亚马逊生成人工智能）；University of Bristol（布里斯托大学）
North Carolina State University（北卡罗来纳州立大学）；Old Dominion University（欧道明大学）；Utah State University（犹他州立大学）
Edge caching is a new paradigm that has been exploited over the past several years to reduce the load for the core network and to enhance the content delivery performance. Many existing caching solutions only consider homogeneous caching placement due to the immense complexity associated with the heterogeneous caching models. Unlike these legacy modeling paradigms, this paper considers heterogeneous content preference of the users with heterogeneous caching models at the edge nodes. Besides, aiming to maximize the cache hit ratio (CHR) in a two-tier heterogeneous network, we let the edge nodes…
Universitat Politècnica de València（瓦伦西亚理工大学）；Coventry University（考文垂大学）
Nowadays, there is increasing interest in the development of teamwork skills in the educational context. This growing interest is motivated by its pedagogical effectiveness and the fact that, in labour contexts, enterprises organize their employees in teams to carry out complex projects. Despite its crucial importance in the classroom and industry, there is a lack of support for the team formation process. Not only do many factors influence team performance, but the problem becomes exponentially costly if teams are to be optimized. In this article, we propose a tool whose aim it is to cover su…
FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources
School of Computing and Informatics, University of Louisiana at Lafayette, USA（路易斯安那州立大学拉斐特分校计算机与信息学院）；Department of Computer and Information Sciences, University of Delaware, USA（德雷塞尔大学计算机与信息科学系）；Department of Computer Science, University of Illinois at Urbana-Champaign, USA（伊利诺伊大学厄巴纳-香槟分校计算机科学系）
National University of Sciences and Technology（国立科技大学）；Kings College London（伦敦国王学院）；Air University（航空大学）；National University of Computer and Emerging Sciences（国立计算机与新兴科学大学）
5th generation networks are envisioned to provide seamless and ubiquitous connection to 1000-fold more devices and is believed to provide ultra-low latency and higher data rates up to tens of Gbps. Different technologies enabling these requirements are being developed including mmWave communications, Massive MIMO and beamforming, Device to Device (D2D) communications and Heterogeneous Networks. D2D communication is a promising technology to enable applications requiring high bandwidth such as online streaming and online gaming etc. It can also provide ultra- low latencies required for applicat…
Guided Collaboration in Heterogeneous LLM-Based Multi-Agent Systems via Entropy-Based Understanding Assessment and Experience Retrieval
Faculty of Data Science, City University of Macau（数据科学学院，澳门城市大学）；Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences)（计算能力网络与信息安全重点实验室，教育部，山东计算机科学中心，齐鲁工业大学（山东科学院））；Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing, Shandong Fundamental Research Center for Computer Science（山东省计算能力互联网与服务计算重点实验室，山东省计算机科学基础研究中心）
Universitat Pompeu Fabra（庞培法布拉大学）；ICREA（加泰罗尼亚高等研究院）；Institute for Bioengineering of Catalonia (IBEC)（加泰罗尼亚生物工程研究所）；Barcelona Institute of Science and Technology (BIST)（巴塞罗那科学技术研究所）
In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment. We support this claim by analyzing the recent advances of the field. Regarding integration, we note that the most impactful recent contributions have been made possible through the integration of recent Machine Learning methods (based in particular on Deep Learning and Recurrent Neural Networks) with more traditional ones (e.g. Monte-Carlo tree search, goal babbling exploration or addressable memory systems). Regarding embodiment, we note that the traditional benchma…
Institución Universitaria Pascual Bravo（帕斯夸尔·布拉沃大学学院）；Visión Real Cognitiva S. A. S.（真实认知视觉公司）；Vienna University of Technology（维也纳技术大学）
The new computational paradigm of conceptual computation has been introduced in the research program of Artificial Mathematical Intelligence. We provide the explicit artificial generation (or conceptual computation) for the fundamental mathematical notion of topological groups. Specifically, we start with two basic notions belonging to topology and abstract algebra, and we describe recursively formal specifications in the Common Algebraic Specification Language (CASL). The notion of conceptual blending between such conceptual spaces can be materialized computationally in the Heterogeneous Tool…
Tangled Program Graph (TPG) is a reinforcement learning technique based on genetic programming concepts. On state-of-the-art learning environments, TPGs have been shown to offer comparable competence with Deep Neural Networks (DNNs), for a fraction of their computational and storage cost. This lightness of TPGs, both for training and inference, makes them an interesting model to implement Artificial Intelligences (AIs) on embedded systems with limited computational and storage resources. In this paper, we introduce the Gegelati library for TPGs. Besides introducing the general concepts and fea…
Karlsruhe Insitute of Technology (KIT)（卡尔斯鲁厄理工学院）；German Cancer Research Centre (DKFZ)（德国癌症研究中心）
With the rise of AI in recent years and the increase in complexity of the models, the growing demand in computational resources is starting to pose a significant challenge. The need for higher compute power is being met with increasingly more potent accelerators and the use of large compute clusters. However, the gain in prediction accuracy from large models trained on distributed and accelerated systems comes at the price of a substantial increase in energy demand, and researchers have started questioning the environmental friendliness of such AI methods at scale. Consequently, energy efficie…
Optimising for Flourishing: Flourishing Metrics and Return on Flourishing as Success Criteria for Artificial Intelligence and Post-AGI Economic Systems
University of California, San Diego（加利福尼亚大学圣迭戈分校）；Admiralty（阿德默勒尔蒂）
Influenced by the advances in data and computing, the scientific practice increasingly involves machine learning and artificial intelligence driven methods which requires specialized capabilities at the system-, science- and service-level in addition to the conventional large-capacity supercomputing approaches. The latest distributed architectures built around the composability of data-centric applications led to the emergence of a new ecosystem for container coordination and integration. However, there is still a divide between the application development pipelines of existing supercomputing …
Department of Computer Applications in Science \& Engineering, BARCELONA Supercomputing Center, 08034 Barcelona, Spain Escuela Técnica Superior de Ingeniería (ICAI), Universidad Pontificia Comillas, 28015 Madrid, Spain Human Centered AI, Data \& Software, LUXEMBOURG Institute of Science
In the Internet of Things (IoT) era, billions of sensors and devices collect and process data from the environment, transmit them to cloud centers, and receive feedback via the internet for connectivity and perception. However, transmitting massive amounts of heterogeneous data, perceiving complex environments from these data, and then making smart decisions in a timely manner are difficult. Artificial intelligence (AI), especially deep learning, is now a proven success in various areas including computer vision, speech recognition, and natural language processing. AI introduced into the IoT h…
Chongqing University of Posts and Telecommunications（重庆邮电大学）；University of Guelph（圭尔夫大学）；Hosei University（法政大学）
Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should be offered by 6G to meet mobile user expectations. Artificial intelligence (AI) is considered as one of the most important components in 6G. Then AI-based trust management is a promising paradigm to provide trusted and reliable services. In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. Some typical AI-based trust management schemes are first revi…
