scholarly journals Reasoning about Actions in a Multiagent Domain

2001 ◽  
pp. 237-248 ◽  
Author(s):  
Laura Giordano ◽  
Alberto Martelli ◽  
Camilla Schwind
Keyword(s):  
Reasoning About Actions ◽  
Multiagent Domain

Reasoning about actions with loops via Hoare logic

2016 ◽  
Vol 10 (5) ◽  
pp. 870-888 ◽  
Author(s):  
Jiankun He ◽  
Xishun Zhao
Keyword(s):  
Hoare Logic ◽  
Reasoning About Actions

scholarly journals Determining Action Reversibility in STRIPS Using Answer Set and Epistemic Logic Programming

2021 ◽  
pp. 1-17
Author(s):  
WOLFGANG FABER ◽  
MICHAEL MORAK ◽  
LUKÁŠ CHRPA
Keyword(s):  
Logic Programming ◽  
Epistemic Logic ◽  
Answer Set Programming ◽  
Reasoning About Actions ◽  
Original State ◽  
Computational Problem ◽  
Compare And Contrast ◽  
Answer Set

Abstract In the context of planning and reasoning about actions and change, we call an action reversible when its effects can be reverted by applying other actions, returning to the original state. Renewed interest in this area has led to several results in the context of the PDDL language, widely used for describing planning tasks. In this paper, we propose several solutions to the computational problem of deciding the reversibility of an action. In particular, we leverage an existing translation from PDDL to Answer Set Programming (ASP), and then use several different encodings to tackle the problem of action reversibility for the STRIPS fragment of PDDL. For these, we use ASP, as well as Epistemic Logic Programming (ELP), an extension of ASP with epistemic operators, and compare and contrast their strengths and weaknesses.

An Answer Set Programming Framework for Reasoning about Agents' Beliefs and Truthfulness of Statements

2020 ◽  
Author(s):  
Marcello Balduccini ◽  
Michael Gelfond ◽  
Enrico Pontelli ◽  
Tran Cao Son
Keyword(s):  
Answer Set Programming ◽  
Cyber Physical Systems ◽  
Belief State ◽  
Third Party ◽  
Default Reasoning ◽  
Physical Systems ◽  
Reasoning About Actions ◽  
Programming Framework ◽  
Man In The Middle ◽  
Answer Set

The paper proposes a framework for capturing how an agent’s beliefs evolve over time in response to observations and for answering the question of whether statements made by a third party can be believed. The basic components of the framework are a formalism for reasoning about actions, changes, and observations and a formalism for default reasoning. The paper describes a concrete implementation that leverages answer set programming for determining the evolution of an agent's ``belief state'', based on observations, knowledge about the effects of actions, and a theory about how these influence an agent's beliefs. The beliefs are then used to assess whether statements made by a third party can be accepted as truthful. The paper investigates an application of the proposed framework in the detection of man-in-the-middle attacks targeting computers and cyber-physical systems. Finally, we briefly discuss related work and possible extensions.

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