A Unifying Framework for Probabilistic Belief Revision

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2017/190 ◽

2017 ◽

Cited By ~ 1

Author(s):

Zhiqiang Zhuang ◽

James Delgrande ◽

Abhaya Nayak ◽

Abdul Sattar

Keyword(s):

Belief Revision ◽

Representation Theorem ◽

Probabilistic Logic ◽

Basic Principles ◽

Probabilistic Information ◽

Probabilistic Setting ◽

Revision Function

In this paper we provide a general, unifying framework for probabilistic belief revision. We first introduce a probabilistic logic called p-logic that is capable of representing and reasoning with basic probabilistic information. With p-logic as the background logic, we define a revision function called p-revision that resembles partial meet revision in the AGM framework. We provide a representation theorem for p-revision which shows that it can be characterised by the set of basic AGM revision postulates. P-revision represents an "all purpose" method for revising probabilistic information that can be used for, but not limited to, the revision problems behind Bayesian conditionalisation, Jeffrey conditionalisation, and Lewis's imaging. Importantly, p-revision subsumes all three approaches indicating that Bayesian conditionalisation, Jeffrey conditionalisation, and Lewis' imaging all obey the basic principles of AGM revision. As well our investigation sheds light on the corresponding operation of AGM expansion in the probabilistic setting.

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On uniform belief revision

Journal of Logic and Computation ◽

10.1093/logcom/exaa058 ◽

2020 ◽

Vol 30 (7) ◽

pp. 1357-1376

Author(s):

Theofanis Aravanis

Keyword(s):

Present Article ◽

Belief Revision ◽

Possible Worlds ◽

Belief Change ◽

Rational Belief ◽

Iterated Revision ◽

Interesting Class ◽

Total Preorder ◽

Revision Function

Abstract Rational belief-change policies are encoded in the so-called AGM revision functions, defined in the prominent work of Alchourrón, Gärdenfors and Makinson. The present article studies an interesting class of well-behaved AGM revision functions, called herein uniform-revision operators (or UR operators, for short). Each UR operator is uniquely defined by means of a single total preorder over all possible worlds, a fact that in turn entails a significantly lower representational cost, relative to an arbitrary AGM revision function, and an embedded solution to the iterated-revision problem, at no extra representational cost. Herein, we first demonstrate how weaker, more expressive—yet, more representationally expensive—types of uniform revision can be defined. Furthermore, we prove that UR operators, essentially, generalize a significant type of belief change, namely, parametrized-difference revision. Lastly, we show that they are (to some extent) relevance-sensitive, as well as that they respect the so-called principle of kinetic consistency.

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Models of abduction

Revista Eletrônica Informação e Cognição (Cessada) ◽

10.36311/1807-8281.2000.v2n1.705 ◽

1969 ◽

Vol 2 (1) ◽

Author(s):

Paul Bourgine

Keyword(s):

Cognitive Science ◽

Belief Revision ◽

Representation Theorem ◽

The Other

The aim of this paper is to sketch a theory of abduction with its relations with deduction and induction in the sense of the second Peirce. The relation of abduction is seen as a relation which is in some sense reciprocal to deduction. Furthermore, this conception of abduction is directly compatible with the conception of induction underlying belief revision. The main result is a representation theorem which unifies the various meanings of abduction. This theorem has two faces, one axiomatic and the other geometric, which are equivalent. This meaning of abduction is expressed through models from the three main paradigms of cognition ; these models aim at establishing its adequation for the cognitive science.

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A Probabilistic Logic for Resource-Bounded Multi-Agent Systems

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2019/74 ◽

2019 ◽

Cited By ~ 1

Author(s):

Hoang Nga Nguyen ◽

Abdur Rakib

Keyword(s):

Temporal Logic ◽

Probabilistic Reasoning ◽

Resource Constraints ◽

Probabilistic Logic ◽

World Systems ◽

Multi Agent Systems ◽

Coalition Logic ◽

Resource Requirements ◽

Probabilistic Setting ◽

Multi Agent

Resource-bounded alternating-time temporal logic (RB-ATL), an extension of Coalition Logic (CL) and Alternating-time Temporal Logic (ATL), allows reasoning about resource requirements of coalitions in concurrent systems. However, many real-world systems are inherently probabilistic as well as resource-bounded, and there is no straightforward way of reasoning about their unpredictable behaviours. In this paper, we propose a logic for reasoning about coalitional power under resource constraints in the probabilistic setting. We extend RB-ATL with probabilistic reasoning and provide a standard algorithm for the model-checking problem of the resulting logic Probabilistic Resource-Bounded ATL (pRB-ATL).

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Verifying Emergence of Bounded Time Properties in Probabilistic Swarm Systems

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2018/56 ◽

2018 ◽

Author(s):

Alessio Lomuscio ◽

Edoardo Pirovano

Keyword(s):

Decision Problems ◽

Probabilistic Logic ◽

Emergent Properties ◽

Probabilistic Setting

We introduce a parameterised semantics for reasoning about swarms as unbounded collections of agents in a probabilistic setting. We develop a method for the formal identification of emergent properties, expressed in a fragment of the probabilistic logic PCTL. We introduce algorithms for solving the related decision problems and show their correctness. We present an implementation and evaluate its performance on an ant coverage algorithm.

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Current Issues: Evidence-Based Practice for the Real World: Thoughts on Clinical Education in Communication Disorders

Perspectives on Administration and Supervision ◽

10.1044/aas20.3.100 ◽

2010 ◽

Vol 20 (3) ◽

pp. 100-105 ◽

Cited By ~ 3

Author(s):

Anne K. Bothe

Keyword(s):

Clinical Education ◽

Real World ◽

Evidence Based Practice ◽

Communication Disorders ◽

University Faculty ◽

Evidence Based ◽

Speech Language Pathology ◽

Basic Principles ◽

The Real ◽

Language Pathology

This article presents some streamlined and intentionally oversimplified ideas about educating future communication disorders professionals to use some of the most basic principles of evidence-based practice. Working from a popular five-step approach, modifications are suggested that may make the ideas more accessible, and therefore more useful, for university faculty, other supervisors, and future professionals in speech-language pathology, audiology, and related fields.

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