Luis Gustavo Nardin – författare

Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances. Sections provide readers with practical solutions at an architectural level, with solutions presented on the distribution of the learning process and the utilization of machine learning models in a distributed system, tools that enable the distribution and interaction of artificial learning entities, how multi-agent systems and machine learning can be combined, the physical embodiment of intelligent agents, and the interaction of intelligent computing units bound to physical space.Following sections emphasize the challenges that are common to all scenarios and solutions that apply in a wider range of cases. This book does not analyze the internal workings of machine learning models (for instance, in the case of multi-agent reinforcement learning), but instead provides readers with an overview of the challenges brought by the need of artificially intelligent entities to interact with other entities and with their environments, along with practical solutions at an architectural level.Presents leading-edge insights on the diverse ways artificial intelligence is distributed, along with real-world application examplesOffers readers a summary of the challenges posed by the necessity for artificially intelligent entities to engage with other entities and their surroundingsProposes practical architectural-level solutionsExplores communication in local networks, on the web, and within physical environmentsExamines machine learning distributed across a network into software agents using machine learning models to make decisions, and into agents working on the web, in socio-technical networks, and in AI embodied in robots

Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances. Sections provide readers with practical solutions at an architectural level, with solutions presented on the distribution of the learning process and the utilization of machine learning models in a distributed system, tools that enable the distribution and interaction of artificial learning entities, how multi-agent systems and machine learning can be combined, the physical embodiment of intelligent agents, and the interaction of intelligent computing units bound to physical space.Following sections emphasize the challenges that are common to all scenarios and solutions that apply in a wider range of cases. This book does not analyze the internal workings of machine learning models (for instance, in the case of multi-agent reinforcement learning), but instead provides readers with an overview of the challenges brought by the need of artificially intelligent entities to interact with other entities and with their environments, along with practical solutions at an architectural level. - Presents leading-edge insights on the diverse ways artificial intelligence is distributed, along with real-world application examples- Offers readers a summary of the challenges posed by the necessity for artificially intelligent entities to engage with other entities and their surroundings- Proposes practical architectural-level solutions- Explores communication in local networks, on the web, and within physical environments- Examines machine learning distributed across a network into software agents using machine learning models to make decisions, and into agents working on the web, in socio-technical networks, and in AI embodied in robots

The volume LNAI 15398 constitutes the revised selected papers of the 28th International Workshop on Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems, COINE 2024, held in Auckland, New Zealand, on May 7, 2024. The 9 full papers were carefully reviewed and selected from 10 submissions. The workshop focuses on both scientific and technological aspects of social coordination, organizational theory, artificial (electronic) institutions, and normative and ethical MAS.

This book constitutes the thoroughly refereed post-conference proceedings of the 17th International Workshop on Multi-Agent-Based Simulation, MABs 2016, held in Singapore, in May 2016. The workshop was held in Conjunction with the 15th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2016. The 10 revised full papers included in this volume were carefully selected from 15 submissions. The topic of the papers is about modeling and analyzing multi-agent systems and applying agent-based  simulation techniques to real-world problems, focusing on the confluence of socio-technical- natural sciences and multi-agents systems with a strong application/empirical vein. Special emphasis is given on exploratory agent-based simulation as a principled way of undertaking scientific research in the social sciences and on using social theories as an inspiration to new frameworks and developments in multi-agent systems.