PRIMA 2018: Principles and Practice of Multi-Agent Systems PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download PRIMA 2018: Principles and Practice of Multi-Agent Systems PDF full book. Access full book title PRIMA 2018: Principles and Practice of Multi-Agent Systems by Tim Miller. Download full books in PDF and EPUB format.
Author: Tim Miller
Publisher: Springer
ISBN: 3030030989
Category : Computers
Languages : en
Pages : 687
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 21st International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2018, held in Tokyo, Japan, in October/November 2018. The 27 full papers presented and 31 short papers were carefully reviewed and selected from 103 submissions. PRIMA presents subjects in many application domains, particularly in e-commerce, and also in planning, logistics, manufacturing, robotics, decision support, transportation, entertainment, emergency relief and disaster management, and data mining and analytics.
Author: Tim Miller
Publisher: Springer
ISBN: 3030030989
Category : Computers
Languages : en
Pages : 687
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 21st International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2018, held in Tokyo, Japan, in October/November 2018. The 27 full papers presented and 31 short papers were carefully reviewed and selected from 103 submissions. PRIMA presents subjects in many application domains, particularly in e-commerce, and also in planning, logistics, manufacturing, robotics, decision support, transportation, entertainment, emergency relief and disaster management, and data mining and analytics.
Author: Takahiro Uchiya
Publisher: Springer Nature
ISBN: 3030693228
Category : Computers
Languages : en
Pages : 440
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020, held in Nagoya, Japan, in November 2020. The 19 full papers presented and 13 short papers were carefully reviewed and selected from 50 submissions. Due to COVID-19, the conference was held online. The conference covers a wide range of ranging from foundations of agent theory and engineering aspects of agent systems, to emerging interdisciplinary areas of agent-based research.
Author: Reyhan Aydoğan
Publisher: Springer Nature
ISBN: 3031212037
Category : Computers
Languages : en
Pages : 714
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020, held in hybrid mode in Valencia, Spain, in November 2022. The 31 full papers presented together with 15 short papers and 1 demo paper were carefully reviewed and selected from 100 submissions. The conference covers a wide range of ranging from foundations of agent theory and engineering aspects of agent systems, to emerging interdisciplinary areas of agent-based research.
Author: Matteo Baldoni
Publisher: Springer Nature
ISBN: 3030337928
Category : Computers
Languages : en
Pages : 660
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019, held in Turin, Italy, in October 2019. The 25 full papers presented and 25 short papers were carefully reviewed and selected from 112 submissions. The papers presented at the PRIMA 2019 conference focus on the following topics: Logic and Reasoning, Engineering Multi-Agent Systems, Agent-Based Modeling and Simulation, Collaboration and Coordination, Economic Paradigms, Human-Agent Interaction, Decentralized Paradigms, and Application Domains for Multi-Agent Systems.
Author: Mehmet Kaya
Publisher: Springer Nature
ISBN: 3030336980
Category : Science
Languages : en
Pages : 245
Get Book Here
Book Description
This book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.
Author: Meir Kalech
Publisher: World Scientific
ISBN: 9811239932
Category : Computers
Languages : en
Pages : 457
Get Book Here
Book Description
Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)
Author: K. Gal
Publisher: IOS Press
ISBN: 164368437X
Category : Computers
Languages : en
Pages : 3328
Get Book Here
Book Description
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
Author: Ryuta Arisaka
Publisher: Springer Nature
ISBN: 3031773675
Category :
Languages : en
Pages : 470
Get Book Here
Book Description
Author: Fredrik Präntare
Publisher: Linköping University Electronic Press
ISBN: 9180756018
Category :
Languages : en
Pages : 184
Get Book Here
Book Description
Allocating resources, goods, agents (e.g., humans), expertise, production, and assets is one of the most influential and enduring cornerstone challenges at the intersection of artificial intelligence, operations research, politics, and economics. At its core—as highlighted by a number of seminal works [181, 164, 125, 32, 128, 159, 109, 209, 129, 131]—is a timeless question: How can we best allocate indivisible entities—such as objects, items, commodities, jobs, or personnel—so that the outcome is as valuable as possible, be it in terms of expected utility, fairness, or overall societal welfare? This thesis confronts this inquiry from multiple algorithmic viewpoints, focusing on the value-maximizing combinatorial assignment problem: the optimization challenge of partitioning a set of indivisibles among alternatives to maximize a given notion of value. To exemplify, consider a scenario where an international aid organization is responsible for distributing medical resources, such as ventilators and vaccines, and allocating medical personnel, including doctors and nurses, to hospitals during a global health crisis. These resources and personnel—inherently indivisible and non-fragmentable—necessitate an allocation process designed to optimize utility and fairness. Rather than using manual interventions and ad-hoc methods, which often lack precision and scalability, a rigorously developed and demonstrably performant approach can often be more desirable. With this type of challenge in mind, our thesis begins through the lens of computational complexity theory, commencing with an initial insight: In general, under prevailing complexity-theoretic assumptions (P ≠ NP), it is impossible to develop an efficient method guaranteeing a value-maximizing allocation that is better than “arbitrarily bad”, even under severely constraining limitations and simplifications. This inapproximability result not only underscores the problem’s complexity but also sets the stage for our ensuing work, wherein we develop novel algorithms and concise representations for utilitarian, egalitarian, and Nash welfare maximization problems, aimed at maximizing average, equitable, and balanced utility, respectively. For example, we introduce the synergy hypergraph—a hypergraph-based characterization of utilitarian combinatorial assignment—which allows us to prove several new state-of-the-art complexity results to help us better understand how hard the problem is. We then provide efficient approximation algorithms and (non-trivial) exponential-time algorithms for many hard cases. In addition, we explore complexity bounds for generalizations with interdependent effects between allocations, known as externalities in economics. Natural applications in team formation, resource allocation, and combinatorial auctions are also discussed; and a novel “bootstrapped” dynamic-programming method is introduced. We then transition from theory to practice as we shift our focus to the utilitarian variant of the problem—an incarnation of the problem particularly applicable to many real-world scenarios. For this variation, we achieve substantial empirical algorithmic improvements over existing methods, including industry-grade solvers. This work culminates in the development of a new hybrid algorithm that combines dynamic programming with branch-and-bound techniques that is demonstrably faster than all competing methods in finding both optimal and near-optimal allocations across a wide range of experiments. For example, it solves one of our most challenging problem sets in just 0.25% of the time required by the previous best methods, representing an improvement of approximately 2.6 orders of magnitude in processing speed. Additionally, we successfully integrate and commercialize our algorithm into Europa Universalis IV—one of the world’s most popular strategy games, with a player base exceeding millions. In this dynamic and challenging setting, our algorithm efficiently manages complex strategic agent interactions, highlighting its potential to improve computational efficiency and decision-making in real-time, multi-agent scenarios. This also represents one of the first instances where a combinatorial assignment algorithm has been applied in a commercial context. We then introduce and evaluate several highly efficient heuristic algorithms. These algorithms—while lacking provable quality guarantees—employ general-purpose heuristic and random-sampling techniques to significantly outperform existing methods in both speed and quality in large-input scenarios. For instance, in one of our most challenging problem sets, involving a thousand indivisibles, our best algorithm generates outcomes that are 99.5% of the expected optimal in just seconds. This performance is particularly noteworthy when compared to state-of-the-art industry-grade solvers, which struggle to produce any outcomes under similar conditions. Further advancing our work, we employ novel machine learning techniques to generate new heuristics that outperform the best hand-crafted ones. This approach not only showcases the potential of machine learning in combinatorial optimization but also sets a new standard for combinatorial assignment heuristics to be used in real-world scenarios demanding rapid, high-quality decisions, such as in logistics, real-time tactics, and finance. In summary, this thesis bridges many gaps between the theoretical and practical aspects of combinatorial assignment problems such as those found in coalition formation, combinatorial auctions, welfare-maximizing resource allocation, and assignment problems. It deepens the understanding of the computational complexities involved and provides effective and improved solutions for longstanding real-world challenges across various sectors—providing new algorithms applicable in fields ranging from artificial intelligence to logistics, finance, and digital entertainment, while simultaneously paving the way for future work in computational problem-solving and optimization.
Author: Mohd Hafiz Mohd
Publisher: Springer Nature
ISBN: 9811626294
Category : Mathematics
Languages : en
Pages : 440
Get Book Here
Book Description
This book discusses the latest progresses and developments on complex systems research and intends to give an exposure to prospective readers about the theoretical and practical aspects of mathematical modelling, numerical simulation and agent-based modelling frameworks. The main purpose of this book is to emphasize a unified approach to complex systems analysis, which goes beyond to examine complicated phenomena of numerous real-life systems; this is done by investigating a huge number of components that interact with each other at different (microscopic and macroscopic) scales; new insights and emergent collective behaviours can evolve from the interactions between individual components and also with their environments. These tools and concepts permit us to better understand the patterns of various real-life systems and help us to comprehend the mechanisms behind which distinct factors shaping some complex systems phenomena being influenced. This book is published in conjunction with the International Workshop on Complex Systems Modelling & Simulation 2019 (CoSMoS 2019): IoT & Big Data Integration. This international event was held at the Universiti Sains Malaysia Main Campus, Penang, Malaysia, from 8 to 11 April 2019. This book appeals to readers interested in complex systems research and other related areas such as mathematical modelling, numerical simulation and agent-based modelling frameworks.
