By Francesca Rossi, Kristen Brent Venable, Toby Walsh
Computational social selection is an increasing box that merges classical subject matters like economics and vote casting idea with extra glossy themes like man made intelligence, multiagent structures, and computational complexity. This e-book presents a concise advent to the most study traces during this box, protecting facets comparable to choice modelling, uncertainty reasoning, social selection, good matching, and computational features of choice aggregation and manipulation. The booklet is established round the thought of choice reasoning, either within the single-agent and the multi-agent atmosphere. It offers the most ways to modeling and reasoning with personal tastes, with specific recognition to 2 renowned and strong formalisms, smooth constraints and CP-nets. The authors ponder choice elicitation and numerous sorts of uncertainty in gentle constraints. They evaluate the main appropriate ends up in vote casting, with precise realization to computational social selection. eventually, the booklet considers personal tastes in matching difficulties. The booklet is meant for college students and researchers who could be attracted to an creation to choice reasoning and multi-agent choice aggregation, and who need to know the fundamental notions and ends up in computational social selection. desk of Contents: creation / choice Modeling and Reasoning / Uncertainty in choice Reasoning / Aggregating personal tastes / reliable Marriage difficulties
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Extra info for A Short Introduction to Preferences: Between AI and Social Choice (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Determining if one outcome is preferred to another (that is, a dominance query) is PSPACE-complete for acyclic CP-nets, even if feature domains have just two values : intuitively, to check whether an outcome is preferred to another one, one should find a chain of worsening flips, and these chains can be exponentially long. Various extensions of the notion of CP-net have been defined and studied over the years. For example, TCP-nets introduce the notion of trade-offs in CP-nets based on the idea that variables may have different importance levels .
In the context of IVSCSPs, a scenario is a soft constraint problem obtained by choosing one element in each preference interval. 1. 1. Scenarios can be used to assess the robustness of different solutions. In particular, the two following notions of optimal solutions arise naturally. Possibly Optimal Solution. An assignment s to all the variables is possibly optimal if it is optimal in some scenario. In other words, there exists a choice of preferences in the intervals such that s is an optimal solution of the resulting SCSP.
These total orders are shown close to the node representing the feature. Thus, this CP-net includes the following cp-statements: fish is preferred to meat; peaches are preferred to strawberries; white wine is preferred to red wine if fish is served; otherwise, red wine is preferred to white wine. 5: A CP-net and its outcome ordering. 2 PREFERENCE ORDERING The ceteris paribus interpretation. A CP-net induces an ordering over the variable assignments, which is based on the ceteris paribus interpretation of the conditional preference statements.
A Short Introduction to Preferences: Between AI and Social Choice (Synthesis Lectures on Artificial Intelligence and Machine Learning) by Francesca Rossi, Kristen Brent Venable, Toby Walsh