5,514 research outputs found
A Strategy for Implementing description Temporal Dynamic Algorithms in Dynamic Knowledge Graphs by SPIN
Planning and reasoning about actions and processes, in addition to reasoning
about propositions, are important issues in recent logical and computer science
studies. The widespread use of actions in everyday life such as IoT, semantic
web services, etc., and the limitations and issues in the action formalisms are
two factors that lead us to study how actions are represented.
Since 2007, there have been some ideas to integrate Description Logic (DL)
and action formalisms for representing both static and dynamic knowledge.
Meanwhile, time is an important factor in dynamic situations, and actions
change states over time. In this study, on the one hand, we examined related
logical structures such as extensions of description logics (DLs), temporal
formalisms, and action formalisms. On the other hand, we analyzed possible
tools for designing and developing the Knowledge and Action Base (KAB).
For representation and reasoning about actions, we embedded actions into DLs
(such as Dynamic-ALC and its extensions). We propose a terminable algorithm for
action projection, planning, checking the satisfiability, consistency,
realizability, and executability, and also querying from KAB. Actions in this
framework were modeled with SPIN and added to state space. This framework has
also been implemented as a plugin for the Prot\'eg\'e ontology editor.
During the last two decades, various algorithms have been presented, but due
to the high computational complexity, we face many problems in implementing
dynamic ontologies. In addition, an algorithm to detect the inconsistency of
actions' effects was not explicitly stated. In the proposed strategy, the
interactions of actions with other parts of modeled knowledge, and a method to
check consistency between the effects of actions are presented. With this
framework, the ramification problem can be well handled in future works
Reasoning about Action: An Argumentation - Theoretic Approach
We present a uniform non-monotonic solution to the problems of reasoning
about action on the basis of an argumentation-theoretic approach. Our theory is
provably correct relative to a sensible minimisation policy introduced on top
of a temporal propositional logic. Sophisticated problem domains can be
formalised in our framework. As much attention of researchers in the field has
been paid to the traditional and basic problems in reasoning about actions such
as the frame, the qualification and the ramification problems, approaches to
these problems within our formalisation lie at heart of the expositions
presented in this paper
Planning with Incomplete Information
Planning is a natural domain of application for frameworks of reasoning about
actions and change. In this paper we study how one such framework, the Language
E, can form the basis for planning under (possibly) incomplete information. We
define two types of plans: weak and safe plans, and propose a planner, called
the E-Planner, which is often able to extend an initial weak plan into a safe
plan even though the (explicit) information available is incomplete, e.g. for
cases where the initial state is not completely known. The E-Planner is based
upon a reformulation of the Language E in argumentation terms and a natural
proof theory resulting from the reformulation. It uses an extension of this
proof theory by means of abduction for the generation of plans and adopts
argumentation-based techniques for extending weak plans into safe plans. We
provide representative examples illustrating the behaviour of the E-Planner, in
particular for cases where the status of fluents is incompletely known.Comment: Proceedings of the 8th International Workshop on Non-Monotonic
Reasoning, April 9-11, 2000, Breckenridge, Colorad
Metatheory of actions: beyond consistency
Consistency check has been the only criterion for theory evaluation in
logic-based approaches to reasoning about actions. This work goes beyond that
and contributes to the metatheory of actions by investigating what other
properties a good domain description in reasoning about actions should have. We
state some metatheoretical postulates concerning this sore spot. When all
postulates are satisfied together we have a modular action theory. Besides
being easier to understand and more elaboration tolerant in McCarthy's sense,
modular theories have interesting properties. We point out the problems that
arise when the postulates about modularity are violated and propose algorithmic
checks that can help the designer of an action theory to overcome them
Planning actions in robot automated operations
Action planning in robot automated operations requires intelligent task level programming. Invoking intelligence necessiates a typical blackboard based architecture, where, a plan is a vector between the start frame and the goal frame. This vector is composed of partially ordered bases. A partial ordering of bases presents good and bad sides in action planning. Partial ordering demands the use of a temporal data base management system
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