Belief contraction as nonmonotonic inference

2000 ◽  
Vol 65 (2) ◽  
pp. 605-626 ◽  
Author(s):  
Alexander Bochman
Keyword(s):  
Belief Change ◽  
Epistemic State ◽  
Belief Contraction ◽  
Nonmonotonic Inference

AbstractA notion of an epistemic state is introduced as a generalization of common representations suggested for belief change. Based on it, a new kind of nonmonotonic inference relation corresponding to belief contractions is defined. A number of representation results is established that cover both traditional AGM contractions and contractions that do not satisfy recovery.

OUTCOME LEVEL ANALYSIS OF BELIEF CONTRACTION

2013 ◽  
Vol 6 (2) ◽  
pp. 183-204 ◽  
Author(s):  
SVEN OVE HANSSON
Keyword(s):  
Belief Change ◽  
Belief Contraction ◽  
Axiomatic Characterizations ◽  
Outcome Set ◽  
Level Analysis

AbstractThe outcome set of a belief change operator is the set of outcomes that can be obtained with it. Axiomatic characterizations are reported for the outcome sets of the standard AGM contraction operators and eight types of base-generated contraction. These results throw new light on the properties of some of these operators.

scholarly journals Belief Update within Propositional Fragments

2018 ◽  
Vol 61 ◽  
pp. 807-834 ◽  
Author(s):  
Nadia Creignou ◽  
Raïda Ktari ◽  
Odile Papini
Keyword(s):  
Knowledge Representation ◽  
Belief Revision ◽  
Classical Logic ◽  
Propositional Logic ◽  
Belief Change ◽  
Research Area ◽  
Belief Contraction ◽  
Belief Merging ◽  
Change Operation ◽  
Horn Fragment

Belief change within the framework of fragments of propositional logic is one of the main and recent challenges in the knowledge representation research area. While previous research works focused on belief revision, belief merging, and belief contraction, the problem of belief update within fragments of classical logic has not been addressed so far. In the context of revision, it has been proposed to refine existing operators so that they operate within propositional fragments, and that the result of revision remains in the fragment under consideration. This approach is not restricted to the Horn fragment but also applicable to other propositional fragments like Krom and affine fragments. We generalize this notion of refinement to any belief change operator. We then focus on a specific belief change operation, namely belief update. We investigate the behavior of the refined update operators with respect to satisfaction of the KM postulates and highlight differences between revision and update in this context.

Belief Contraction in Non-classical logics as Hyperintensional Belief Change

2021 ◽  
Author(s):  
Marlo Souza ◽  
Renata Wassermann
Keyword(s):  
Belief Revision ◽  
General Framework ◽  
Belief Change ◽  
Description Logics ◽  
Belief Contraction

AGM's belief revision is one of the main paradigms in the study of belief change operations. Despite its popularity and importance to the area, it is well recognised that AGM's work relies on a strong idealisation of the agent's capabilities and the nature of beliefs themselves. Particularly, it is recognised in the literature that Belief and Knowledge are hyperintensional attitudes, i.e. they can differentiate between contents that are necessarily equivalent, but to our knowledge, only a few works have explicitly considered how hyperintensionality affects belief change. This work investigates abstract operations of hyperintensional belief change and their connection to belief change in non-classical logics, such as belief contraction operations for Horn Logics and Description Logics. Our work points to hyperintensional belief change as a general framework to unify results in belief change for non-classical logics.

scholarly journals Iterated contraction of propositions and conditionals under the principle of conditional preservation

10.29007/3q8l ◽  
2018 ◽  
Author(s):  
Gabriele Kern-Isberner ◽  
Tanja Bock ◽  
Kai Sauerwald ◽  
Christoph Beierle
Keyword(s):  
Belief Revision ◽  
Belief Change ◽  
Ranking Function ◽  
Ranking Functions ◽  
Belief Contraction ◽  
Seminal Work ◽  
Iterated Belief Revision ◽  
Iterated Contraction

Research on iterated belief change has focussed mostly on belief revision, only few papers have addressed iterated belief contraction. Most prominently, Darwiche and Pearl published seminal work on iterated belief revision the leading paradigm of which is the so-called principle of conditional preservation. In this paper, we use this principle in a thoroughly axiomatized form to develop iterated belief contraction operators for Spohn's ranking functions. We show that it allows for setting up constructive approaches to tackling the problem of how to contract a ranking function by a proposition or a conditional, respectively, and that semantic principles can also be derived from it for the purely qualitative case.

scholarly journals Policy learning as complex contagion: how social networks shape organizational beliefs in forest-based climate change mitigation

2021 ◽  
Author(s):  
Antti Gronow ◽  
Maria Brockhaus ◽  
Monica Di Gregorio ◽  
Aasa Karimo ◽  
Tuomas Ylä-Anttila
Keyword(s):  
Social Network ◽  
Social Influence ◽  
Belief Change ◽  
Forest Degradation ◽  
Policy Learning ◽  
Policy Network ◽  
Policy Problem ◽  
Perceived Need ◽  
Organizational Beliefs ◽  
Policy Subsystems

AbstractPolicy learning can alter the perceptions of both the seriousness and the causes of a policy problem, thus also altering the perceived need to do something about the problem. This then allows for the informed weighing of different policy options. Taking a social network perspective, we argue that the role of social influence as a driver of policy learning has been overlooked in the literature. Network research has shown that normatively laden belief change is likely to occur through complex contagion—a process in which an actor receives social reinforcement from more than one contact in its social network. We test the applicability of this idea to policy learning using node-level network regression models on a unique longitudinal policy network survey dataset concerning the Reducing Deforestation and Forest Degradation (REDD+) initiative in Brazil, Indonesia, and Vietnam. We find that network connections explain policy learning in Indonesia and Vietnam, where the policy subsystems are collaborative, but not in Brazil, where the level of conflict is higher and the subsystem is more established. The results suggest that policy learning is more likely to result from social influence and complex contagion in collaborative than in conflictual settings.

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