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Using Decision Theory and Value Alignment to Integrate Analogue and Digital AI
Published in Maurizio Tinnirello, The Global Politics of Artificial Intelligence, 2022
Roughly speaking, social choice theory is the science of group decision-making processes. Historically, since the 1950s, social choice has been a province of politics, economics, and philosophy, but interest has slowly declined since the 1970s such that by 2000, social choice research was primarily relegated to subfield journals in those disciplines. But since the late 1980s, interest in social choice has grown in computer science, such that by the 2000s, it might be reasonable to claim that “sovereignty” of the social choice province was transferred to computer science. For example, at the annual conference of the Association for the Advancement of Artificial Intelligence (AAAI), there is an entire subtopic keyword dedicated to social choice submissions (e.g. “Game Theory and Economic Paradigms: Social Choice/Voting”).2 Because modern social choice started out in the economics and politics literatures, the terminology of the field was based on voting and elections examples. When social choice became a part of computer science, computer science inherited much of this voting and elections language. One thing that should become eminently clear by the end of this chapter is how thoroughly intertwined politics and multiagent AI systems languages have become at the junction of group decision-making. But it is important to note that social choice is more general than just voting in political elections. While the language used carries the artefacts of elections and voting, it can basically be used to understand any group decision-making process where individual entities submit information to a system, where the system then uses this information to decide which action the group should take.
Representing voting rules in Łukasiewicz’s three-valued logic
Published in Journal of Applied Non-Classical Logics, 2022
Following the proof of Arrow’s impossibility theorem (1951), social choice theory developed as the study of the ways in which individual preferences can be aggregated to reach a collective or social preference. For example, given a distribution of votes expressed by the members of a group of people, a voting rule selects the collection of winning candidates or the number of seats won by political parties in representative bodies, like the Parliament or local councils. In the past decades, social choice techniques were applied to many other aggregation problems characterised by common structural features. The simplest case is that of a single person who rates m objects against each of n criteria in order to choose one of them. A more recent example was initiated by List and Pettit (2002): they explored the way in which the judgments held on some interconnected questions by the members of a group can be aggregated to form a collective set of judgments on those questions (List & Polak [2010] and Mongin [2018] are two surveys of the literature on this topic).
Revenue allocation in Formula One: a pairwise comparison approach
Published in International Journal of General Systems, 2021
Dóra Gréta Petróczy, László Csató
Note that the proposed model is similar to the Condorcet-like methods, widely used in social choice theory, only at first sight. For example, Soares de Mello et al. (2015) introduces a so-called Condorcet graph, where the nodes represent the Formula One teams, and there is a directed edge from node i to node j if team i is preferred to team j, that is, if team i is preferred to team j in the majority of races. Therefore, the Condorcet variants take only the pairwise preferences into account but not their intensities. Unsurprisingly, this loss of information often means that the Condorcet method does not provide a strict ranking, while ties between the revenue share of two teams in our model are less frequent (and does not mean any problem).