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Author: James Andreoni
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
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Book Description
Author: James Andreoni
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
Get Book Here
Book Description
Author: James Andreoni
Publisher:
ISBN:
Category : Auctions
Languages : en
Pages : 26
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Book Description
Author: Karl Tuyls
Publisher: Springer
ISBN: 3540779493
Category : Computers
Languages : en
Pages : 263
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Book Description
This book contains selected and revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS), editions 2005, 2006 and 2007, held in Paris, Brussels and Maastricht. The goal of the ALAMAS symposia, and this associated book, is to increase awareness and interest in adaptation and learning for single agents and mul- agent systems, and encourage collaboration between machine learning experts, softwareengineeringexperts,mathematicians,biologistsandphysicists,andgive a representative overviewof current state of a?airs in this area. It is an inclusive forum where researchers can present recent work and discuss their newest ideas for a ?rst time with their peers. Thesymposiaseriesfocusesonallaspectsofadaptiveandlearningagentsand multi-agent systems, with a particular emphasis on how to modify established learning techniques and/or create new learning paradigms to address the many challenges presented by complex real-world problems. These symposia were a great success and provided a forum for the pres- tation of new ideas and results bearing on the conception of adaptation and learning for single agents and multi-agent systems. Over these three editions we received 51 submissions, of which 17 were carefully selected, including one invited paper of this year’s invited speaker Simon Parsons. This is a very c- petitive acceptance rate of approximately 31%, which, together with two review cycles, has led to a high-quality LNAI volume. We hope that our readers will be inspired by the papers included in this volume.
Author: Clemens van Dinther
Publisher: Springer Science & Business Media
ISBN: 3764381132
Category : Computers
Languages : en
Pages : 245
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Book Description
This is one of the first books on the use of software agents to simulate bidding behavior in electronic auctions. It introduces market theory and computational economics together, and gives an overview on the most common and up-to-date agent-based simulation methods. The book will help the reader learn more about simulations in economics in general and common agent-based methods and tools in particular.
Author: Peter Vrancx
Publisher: Springer
ISBN: 364228499X
Category : Computers
Languages : en
Pages : 141
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Book Description
This volume constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Adaptive and Learning Agents, ALA 2011, held at the 10th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2011, in Taipei, Taiwan, in May 2011. The 7 revised full papers presented together with 1 invited talk were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on single and multi-agent reinforcement learning, supervised multiagent learning, adaptation and learning in dynamic environments, learning trust and reputation, minority games and agent coordination.
Author: John Duffy
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
Many internet auction sites implement ascending-bid, second-price auctions. Empirically, last minute or quot;latequot; bidding is frequently observed in quot;hard-closequot; but not in quot;soft-closequot; versions of these auctions. In this paper, we introduce an independent private-value repeated internet auction model to explain this observed difference in bidding behavior. We use finite automata to model the repeated auction strategies. We report results from simulations involving populations of artificial bidders who update their strategies via a genetic algorithm. We show that our model can deliver late or early bidding behavior, depending on the auction closing rule in accordance with the empirical evidence. Among other findings, we observe that hard-close auctions raise less revenue than soft-close auctions. We also investigate interesting properties of the evolving strategies and arrive at some conclusions regarding both auction designs from a market design point of view.
Author: Ana Paula Rocha
Publisher: Springer Nature
ISBN: 3030711587
Category : Computers
Languages : en
Pages : 520
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Book Description
This book contains the revised and extended versions of selected papers from the 12th International Conference on Agents and Artificial Intelligence, ICAART 2020, held in Valletta, Malta, in February 2020. Overall, 45 full papers, 74 short papers, and 56 poster papers were carefully reviewed and selected from 276 initial submissions. 23 of the 45 full papers were selected to be included in this volume. These papers deal with topics such as agents and artificial intelligence.
Author: Deddy Koesrindartoto
Publisher:
ISBN:
Category :
Languages : en
Pages : 65
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Book Description
Author: Michael P. Wellman
Publisher: MIT Press
ISBN: 026223260X
Category : Agents intelligents (Logiciels)
Languages : en
Pages : 251
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Book Description
E-commerce increasingly provides opportunities for autonomous bidding agents: computer programs that bid in electronic markets without direct human intervention. Automated bidding strategies for an auction of a single good with a known valuation are fairly straightforward; designing strategies for simultaneous auctions with interdependent valuations is a more complex undertaking. This book presents algorithmic advances and strategy ideas within an integrated bidding agent architecture that have emerged from recent work in this fast-growing area of research in academia and industry. The authors analyze several novel bidding approaches that developed from the Trading Agent Competition (TAC), held annually since 2000. The benchmark challenge for competing agents--to buy and sell multiple goods with interdependent valuations in simultaneous auctions of different types--encourages competitors to apply innovative techniques to a common task. The book traces the evolution of TAC and follows selected agents from conception through several competitions, presenting and analyzing detailed algorithms developed for autonomous bidding. Autonomous Bidding Agents provides the first integrated treatment of methods in this rapidly developing domain of AI. The authors--who introduced TAC and created some of its most successful agents--offer both an overview of current research and new results. Michael P. Wellman is Professor of Computer Science and Engineering and member of the Artificial Intelligence Laboratory at the University of Michigan, Ann Arbor. Amy Greenwald is Assistant Professor of Computer Science at Brown University. Peter Stone is Assistant Professor of Computer Sciences, Alfred P. Sloan Research Fellow, and Director of the Learning Agents Group at the University of Texas, Austin. He is the recipient of the International Joint Conference on Artificial Intelligence (IJCAI) 2007 Computers and Thought Award.
Author: Herbert Dawid
Publisher: Springer Science & Business Media
ISBN: 3662002116
Category : Business & Economics
Languages : en
Pages : 173
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Book Description
An analysis of the learning behavior of genetic algorithms in economic systems with mutual interaction, such as markets. These systems are characterized by a state-dependent fitness function and - for the first time - mathematical results characterizing the long-term outcome of genetic learning in such systems are provided. The usefulness of such results is illustrated by many simulations in evolutionary games and economic models.
