human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "A model for belief revision"
  Abstract: Abstract   It is generally recognized that the possibility of detecting contradictions and identifying their sources is an important feature of an intelligent system. Systems that are able to detect contradictions, identify their causes, or readjust their knowledge bases to remove the contradiction, called Belief Revision Systems, Truth Maintenance Systems, or Reason Maintenance Systems, have been studied by several researchers in Artificial Intelligence (AI).  In this paper, we present a logic suitable for supporting belief revision systems, discuss the properties that a belief revision system based on this logic will exhibit, and present a particular implementation of our model of a belief revision system.  The system we present differs from most of the systems developed so far in three respects: First, it is based on a logic that was developed to support belief revision systems. Second, it uses the rules of inference of the logic to automatically compute the dependencies among propositions rather than having to force the user to do this, as in many existing systems. Third, it was the first belief revision system whose implementation relies on the manipulation of sets of assumptions, not justifications.

Connected through hyperedge HE-1 (induced by source paper "MULTI - a LISP based multiprocessing system"):
  with members:
    - "An overview of KRL, a Knowledge Representation Language"

Connected through hyperedge HE-2 (induced by source paper "A general framework for reason maintenance"):
  with members:
    - "How to reason defeasibly"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Mathematics