Add to ORKGSearch is one of the most important needs of problem solvers. Usually the problem solvers suffer from retracing conclusions. If a problem solver cached its inference, then it would not need to retrace conclusions that it had already derived earlier in the search. By caching the inferences, the problem solver avoid throwing away useful results and avoid wasting effort rediscovering the same things over and over. In this paper we present a belief revision system for logic programs that can work under the non-monotonic logic
Belief revision is the process of rearranging a knowledge base to preserve global consistency whilst...
We study the problem of evolution of knowledge in a deductive database by formulating this in terms ...
It is argued that the problems of intensional knowledge base updating and incremental concept-learni...
Belief revision has been studied mainly with respect to background logics that are monotonic in char...
We address the problem of belief revision in (nonmonotonic) logic programming under answer set seman...
It is generally recognized that the possibility of detecting contradictions and identifying their so...
The thesis developed here is that reasoning programs which take care to record the logical justifi...
If a new piece of information contradicts our previously held beliefs, we have to revise our beliefs...
With the advance of robots and more intelligent computer programs, belief revision is becoming an in...
In this paper we describe REVISE, an extended logic programming system for revising knowl-edge bases...
Belief revision leads to temporal nonmonotonicity, i.e., the set of beliefs does not grow monotonica...
Nonmonotonic reasoning is intended to apply specifically in situation where the initial information ...
This paper deals with contradictory information in common-sense reasoning. It is often the case that...
Belief revision systems aim at keeping a database consistent. They mostly concentrate on how to reco...
To choose their actions, reasoning programs must be able to make assumptions and subsequently revi...
Belief revision is the process of rearranging a knowledge base to preserve global consistency whilst...
We study the problem of evolution of knowledge in a deductive database by formulating this in terms ...
It is argued that the problems of intensional knowledge base updating and incremental concept-learni...
Belief revision has been studied mainly with respect to background logics that are monotonic in char...
We address the problem of belief revision in (nonmonotonic) logic programming under answer set seman...
It is generally recognized that the possibility of detecting contradictions and identifying their so...
The thesis developed here is that reasoning programs which take care to record the logical justifi...
If a new piece of information contradicts our previously held beliefs, we have to revise our beliefs...
With the advance of robots and more intelligent computer programs, belief revision is becoming an in...
In this paper we describe REVISE, an extended logic programming system for revising knowl-edge bases...
Belief revision leads to temporal nonmonotonicity, i.e., the set of beliefs does not grow monotonica...
Nonmonotonic reasoning is intended to apply specifically in situation where the initial information ...
This paper deals with contradictory information in common-sense reasoning. It is often the case that...
Belief revision systems aim at keeping a database consistent. They mostly concentrate on how to reco...
To choose their actions, reasoning programs must be able to make assumptions and subsequently revi...
Belief revision is the process of rearranging a knowledge base to preserve global consistency whilst...
We study the problem of evolution of knowledge in a deductive database by formulating this in terms ...
It is argued that the problems of intensional knowledge base updating and incremental concept-learni...