Arrow Research search

Author name cluster

Jianbing Ma

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers
2 author rows

Possible papers

5

KR Conference 2012 Short Paper

Revising partial pre-orders with partial pre-orders: A unit-based revision framework

  • Jianbing Ma
  • Salem Benferhat
  • Weiru Liu

(Benferhat, Lagrue, and Papini 2005)). In (Benferhat et al. 2000), the epistemic state, representing initial information, and the input, representing new information, are both total pre-orders. In (Benferhat, Lagrue, and Papini 2005), the initial epistemic state is indeed a partial pre-order, however, the input information is a propositional formula. In (Bochman 2001), different strategies have been proposed to revise an epistemic state represented by a partial pre-order on the possible worlds. However, in this book there are no revision methods for revising a partial pre-order by a partial pre-order. Our revision operations are also totally different from Lang’s works on preference (e. g. (Lang and van der Torre 2008)), and Weydert, Freund and Kern-Isberner’s revision with conditionals (e. g., (Weydert 1994; Freund 1998; Kern-Isberner 2002)). So far in the literature, there is hardly any work that studies the revision of an epistemic state (especially a partial pre-order) being revised by a partial preorder (a new input). The only work we have seen addressing this issue is a recent paper (Tamargo et al. 2011), in which revision of partial orders is studied in a standard expansion and contraction way. But it does not provide concrete revision results because of the use of certain kinds of selection functions. In this paper, we investigate revision strategies for this setting: a partial pre-order revised by another partial preorder. With this perspective, each individual ordering relation (a pair of elements with an ordering connective), which we name unit, contained in the input is itself an important piece of evidence that should be preserved (Ma, Liu, and Hunter 2011). To propose a revision framework for partial pre-orders, we investigate how a revision operator should be designed. Generally speaking, both a priori ordering set, S, and a new input SI can be seen as sets containing individual ordering relations, e. g., the units. So, revision can be carried out by (i) deriving maximal supersets of SI that contain suitable units in S which do not lead to possible contradiction; (ii) by inserting units from SI to S while removing any units that are inconsistent with this insertion; or (iii) by enlarging SI through inserting one unit from S at a time, while maintaining consistency, etc. Based on these intuitions, we propose a family of unit-based revision operators, dubbed extension revision, match revision, inner revision, and outer revision. We prove the equivalence between these operators Belief revision studies strategies about how agents revise their belief states when receiving new evidence. Both in classical belief revision and in epistemic revision, a new input is either in the form of a (weighted) propositional formula or a total pre-order (where the total pre-order is considered as a whole). However, in some real-world applications, a new input can be a partial pre-order where each unit that constitutes the partial pre-order is important and should be considered individually. To address this issue, in this paper, we study how a partial preorder representing the prior epistemic state can be revised by another partial pre-order (the new input) from a different perspective, where the revision is conducted recursively on the individual units of partial pre-orders. We propose different revision operators (rules), dubbed the extension, match, inner and outer revision operators, from different revision points of view. We also analyze several properties for these operators.

AAAI Conference 2010 Conference Paper

A Belief Revision Framework for Revising Epistemic States with Partial Epistemic States

  • Jianbing Ma
  • Weiru Liu
  • Salem Benferhat

Belief revision performs belief change on an agent’s beliefs when new evidence (either of the form of a propositional formula or of the form of a total pre-order on a set of interpretations) is received. Jeffrey’s rule is commonly used for revising probabilistic epistemic states when new information is probabilistically uncertain. In this paper, we propose a general epistemic revision framework where new evidence is of the form of a partial epistemic state. Our framework extends Jeffrey’s rule with uncertain inputs and covers wellknown existing frameworks such as ordinal conditional function (OCF) or possibility theory. We then define a set of postulates that such revision operators shall satisfy and establish representation theorems to characterize those postulates. We show that these postulates reveal common characteristics of various existing revision strategies and are satisfied by OCF conditionalization, Jeffrey’s rule of conditioning and possibility conditionalization. Furthermore, when reducing to the belief revision situation, our postulates can induce most of Darwiche and Pearl’s postulates.

AAAI Conference 2010 Conference Paper

Inducing Probability Distributions from Knowledge Bases with (In)dependence Relations

  • Jianbing Ma
  • Weiru Liu
  • Anthony Hunter

When merging belief sets from different agents, the result is normally a consistent belief set in which the inconsistency between the original sources is not represented. As probability theory is widely used to represent uncertainty, an interesting question therefore is whether it is possible to induce a probability distribution when merging belief sets. To this end, we first propose two approaches to inducing a probability distribution on a set of possible worlds, by extending the principle of indifference on possible worlds. We then study how the (in)dependence relations between atoms can influence the probability distribution. We also propose a set of properties to regulate the merging of belief sets when a probability distribution is output. Furthermore, our merging operators satisfy the well known Konieczny and Pino-Pérez postulates if we use the set of possible worlds which have the maximal induced probability values. Our study shows that taking an induced probability distribution as a merging result can better reflect uncertainty and inconsistency among the original knowledge bases.

ECAI Conference 2008 Conference Paper

A General Model for Epistemic State Revision using Plausibility Measures

  • Jianbing Ma
  • Weiru Liu

In this paper, we present a general revision model on epistemic states based on plausibility measures proposed by Friedman and Halpern. We propose our revision strategy and give some desirable properties, e. g. , the reversible and commutative properties. Moreover, we develop a notion called plausibility kinematics and show that our revision strategy follows plausibility kinematics. Furthermore, we prove that the revision following plausibility kinematics satisfies the principle of minimal change based on some distance measures. Finally, we discuss a revision operator defined for plausibility functions and its relationship with iterated belief revision proposed by Darwiche and Pearl. We show that the revision operator satisfies all the DP postulates when it is Max-Additive.

v2026.09.13