资源分类
》 资源 》论文》On Consensus Extraction

On Consensus Extraction

2019-11-22 | |  91 |   49 |   0
Abstract Computing a consensus is a key task in various AI areas, ranging from belief fusion, social choice, negotiation, etc. In this work, we define consensus operators as functions that deliver parts of the set-theoretical union of the information sources (in propositional logic) to be reconciled, such that no source is logically contradicted. We also investigate different notions of maximality related to these consensuses. From a computational point of view, we propose a generic problem transformation that leads to a method that proves experimentally efficient very often, even for large conflicting sources to be reconciled.

上一篇：Querying Data Graphs with Arithmetical Regular Expressions

下一篇：Temporalized EL Ontologies for Accessing Temporal Data: Complexity of Atomic Queries

用户评价
全部评价

热门资源

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • dynamical system ...

    allows to preform manipulations of heavy or bul...

  • The Variational S...

    Unlike traditional images which do not offer in...