A Syntactic Approach to Revising Epistemic States with Uncertain Inputs

被引：2

作者：

Bauters, Kim ^{[1
]}

Liu, Weiru ^{[1
]}

Hong, Jun ^{[1
]}

Godo, Lluis ^{[1
,2
]}

Sierra, Carles ^{[1
,2
]}

机构：

[1] QUB, Belfast, Antrim, North Ireland

[2] CSIC, IIIA, Bellaterra, Spain

来源：

2014 IEEE 26TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI) | 2014年

基金：

英国工程与自然科学研究理事会;

关键词：

LOGIC;

D O I：

10.1109/ICTAI.2014.32

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Revising its beliefs when receiving new information is an important ability of any intelligent system. However, in realistic settings the new input is not always certain. A compelling way of dealing with uncertain input in an agent-based setting is to treat it as unreliable input, which may strengthen or weaken the beliefs of the agent. Recent work focused on the postulates associated with this form of belief change and on finding semantical operators that satisfy these postulates. In this paper we propose a new syntactic approach for this form of belief change and show that it agrees with the semantical definition. This makes it feasible to develop complex agent systems capable of efficiently dealing with unreliable input in a semantically meaningful way. Additionally, we show that imposing restrictions on the input and the beliefs that are entailed allows us to devise a tractable approach suitable for resource-bounded agents or agents where reactiveness is of paramount importance.

引用

页码：154 / 161

页数：8