Privacy of Existence of Secrets: Introducing Steganographic DCOPs and Revisiting DCOP Frameworks

Here we identify a type of privacy concern in Distributed Constraint Optimization (DCOPs) not previously addressed in literature, despite its importance and impact on the application field: the privacy of existence of secrets. Science only starts where metrics and assumptions are clearly defined. The area of Distributed Constraint Optimization has emerged at the intersection of the multi-agent system community and constraint programming. For the multi-agent community, the constraint optimization problems are an elegant way to express many of the problems occurring in trading and distributed robotics. For the theoretical constraint programming community the DCOPs are a natural extension of their main object of study, the constraint satisfaction problem. As such, the understanding of the DCOP framework has been refined with the needs of the two communities, but sometimes without spelling the new assumptions formally and therefore making it difficult to compare techniques. Here we give a direction to the efforts for structuring concepts in this area.

Recommending the Most Encompassing Opposing and Endorsing Arguments in Debates

Arguments are essential objects in DirectDemocracyP2P, where they can occur both in association with signatures for petitions, or in association with other debated decisions, such as bug sorting by importance. The arguments of a signer on a given issue are grouped into one single justification, are classified by the type of signature (e.g., supporting or opposing), and can be subject to various types of threading. Given the available inputs, the two addressed problems are: (i) how to recommend the best justification, of a given type, to a new voter, (ii) how to recommend a compact list of justifications subsuming the majority of known arguments for (or against) an issue. We investigate solutions based on weighted bipartite graphs.