Chance discovery means discovering chances - the breaking points in systems, the marketing windows in business, etc. It involves determining the significance of some piece of information about an event and then using this new knowledge in decision making. The techniques developed combine data mining methods for finding rare but important events with knowledge management, groupware, and social psychology. The reader will find many applications, such as finding information on the Internet, recognizing changes in customer behavior, detecting the first signs of an imminent earthquake, etc.

This first book dedicated to chance discovery covers the state of the art in the theory and methods and examines typical scenarios, and it thus appeals to researchers working on new techniques and algorithms and also to professionals dealing with real-world applications.

Chance discovery means discovering chances - the breaking points in systems, the marketing windows in business, etc. It involves determining the significance of some piece of information about an event and then using this new knowledge in decision making. The techniques developed combine data mining methods for finding rare but important events with knowledge management, groupware, and social psychology. The reader will find many applications, such as finding information on the Internet, recognizing changes in customer behavior, detecting the first signs of an imminent earthquake, etc. This first book dedicated to chance discovery covers the state of the art in the theory and methods and examines typical scenarios, and it thus appeals to researchers working on new techniques and algorithms and also to professionals dealing with real-world applications.

This book constitutes selected papers presented at the First International Workshop on Deceptive AI, DeceptECAI 2020, held in conjunction with the 24th European Conference on Artificial Intelligence, ECAI 2020, in Santiago de Compostela, Spain, in August 2020, and Second International Workshop on Deceptive AI, DeceptAI 2021, held in conjunction with the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021, in Montreal, Canada, in August 2021. Due to the COVID-19 pandemic both conferences were held in a virtual mode. The 12 papers presented were thoroughly reviewed and selected from the 16 submissions. They present recent developments in the growing area of research in the interface between deception and AI.

This book constitutes the thoroughly reviewed post-proceedings of the 8th International Workshop on Argumentation in Multi-Agent Systems, ArgMas 2011, held in Taipei, Taiwan in May 2011 in association with the 10th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2011). The 8 revised full papers taken from ArgMAS 2011. Also included are 5 invited papers based on presentations on argumentation at the AAMAS 2011 main conference. All together the 13 papers included in the book give a representative overview on current research on argumentation in multi-agent systems. The papers are listed alphabetically by first author within three thematic topics: foundations and theory; argumentation and dialogue; and applications.

This volume contains revised versions of the papers presented at the sixth e- tion of the International Workshop on Argumentation in Multi-Agent Systems, (ArgMAS2009),heldinBudapest,Hungary,inassociationwiththe8thInter- tional Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2009) in May 2009. Previous ArgMAS workshops have been held in New York City, USA (2004),Utrecht, The Netherlands (2005),Hakodate, Japan (2006), Honolulu, USA (2007) and Estoril, Portugal (2008). The event has now clearlyestablisheditselfonthe internationalcalendaramongresearchersinc- putational argument and dialectics. A brief word to explain these topics is in order. Di?erent agents within a multi-agent system (MAS) potentially have di?erential access to information and di?erent capabilities, di?erent beliefs, di?erent preferences and desires, and di?erent goals. A key aspect of the scienti?c and engineering study of mul- agentsystemsthereforehasbeenthedevelopmentofmethodsandproceduresfor identifying, assessing, reconciling, arbitrating between, managing, and mitig- ing suchdi?erences. Marketmechanismsandvotingproceduresaretwo methods fordealing with thesedi?erences. Argumentationisanother. Argumentationcan be understood as the formal interaction of di?erent arguments for and against some conclusion (e. g. , a proposition, an action intention, a preference, etc. ). An agent may use argumentation techniques to perform individual reasoning for itself alone, in order to resolve con?icting evidence or to decide between c- ?icting goals it may have. Two or more agents may also jointly use dialectical argumentationto identify, express,andreconciledi?erencesbetweenthemselves, by means of interactions such as negotiation, persuasion, inquiry, and joint - liberation.

Voting Over a Distributed Ledger: An Interdisciplinary Perspective presents the case that electronic voting can improve accessibility, leading to some positive outcomes. It can also lead to faster counting and can be cost efficient. The authors document the various problems with centralized electronic voting systems and show how the blockchain can potentially overcome these problems. The authors introduce the concept of distributed ledger technology (DLT) (blockchains are a special case of DLT) and how they can improve both the accessibility and trust properties of an online voting system. This monograph is organized as follows. Section 2 focuses on centralized on-line voting systems (i.e., that do not use distributed ledger technology), describing their general architecture and outlining their vulnerable areas for manipulation. Section 3 describes from scratch the distributed ledger technology and how its promising features can be used for online voting. Section 4 focuses on a special case of distributed ledgers, called blockchains, and analyses the multiple ways (consensus protocols) on reaching agreement on voting data. Section 5 discusses a possible conceptualization on using a blockchain based infrastructure for voting systems. Section 6 presents existing blockchain based voting systems by categorizing them according to the extent that they use this technology, concluding with details of a recent academic implementation. Finally, Section 7 concludes with open questions for economists and other social scientists working in this area.