We propose an extension of the heterogeneous multi-context reasoning framework by G. Brewka and T. Eiter, which, in addition to logical contexts of reasoning, also incorporates sub-symbolic contexts of reasoning. The main findings of the paper are a simple extension of the concept of bridge rules to the sub-symbolic case and the concept of bridge rule models that allows for a straightforward enumeration of all equilibria of multi-context systems.
The field of artificial intelligence, research on knowledge representation and reasoning has origina...
In a previous paper, we proposed a first formal and conceptual comparison between the two important ...
Logical AI develops computer programs that represent what they know about the world primarily by log...
In the introductory part, we give a brief overview of the state of the art concerning multi-context ...
We propose a general framework for multi-context reasoning which allows us to combine arbitrary mono...
Abstract. We propose a framework for heterogeneous multi-context systems, in which a special kind of...
Multi-Context Systems (MCS) model, using Computational Logic, distributed systems composed of hetero...
Multi-Context Systems (MCSs) are able to formally model, in Computational Logic, distributed systems...
This paper proposes a way of bridging the gap between symbolic and sub-symbolic reasoning. More prec...
We propose a framework for heterogeneous multi-context systems, in which a special kind of semantic/...
In this work it is presented a logical framework to model some aspects of contextuality; i.e. genera...
A multicontext logic with algebraic structure is proosed, where contexts are either primitive or com...
Since McCarthy`s Turing Award speech, in 1971, the notion of context has been used in Artificial Int...
Abstract: Extending metaphorically the Moisilean idea of “nuanced-reasoning logic ” and adapting it ...
(Conférencier invité) Workshop hosted by the 18th European Conference on Artificial Intelligence ECA...
The field of artificial intelligence, research on knowledge representation and reasoning has origina...
In a previous paper, we proposed a first formal and conceptual comparison between the two important ...
Logical AI develops computer programs that represent what they know about the world primarily by log...
In the introductory part, we give a brief overview of the state of the art concerning multi-context ...
We propose a general framework for multi-context reasoning which allows us to combine arbitrary mono...
Abstract. We propose a framework for heterogeneous multi-context systems, in which a special kind of...
Multi-Context Systems (MCS) model, using Computational Logic, distributed systems composed of hetero...
Multi-Context Systems (MCSs) are able to formally model, in Computational Logic, distributed systems...
This paper proposes a way of bridging the gap between symbolic and sub-symbolic reasoning. More prec...
We propose a framework for heterogeneous multi-context systems, in which a special kind of semantic/...
In this work it is presented a logical framework to model some aspects of contextuality; i.e. genera...
A multicontext logic with algebraic structure is proosed, where contexts are either primitive or com...
Since McCarthy`s Turing Award speech, in 1971, the notion of context has been used in Artificial Int...
Abstract: Extending metaphorically the Moisilean idea of “nuanced-reasoning logic ” and adapting it ...
(Conférencier invité) Workshop hosted by the 18th European Conference on Artificial Intelligence ECA...
The field of artificial intelligence, research on knowledge representation and reasoning has origina...
In a previous paper, we proposed a first formal and conceptual comparison between the two important ...
Logical AI develops computer programs that represent what they know about the world primarily by log...