The knowledge that must be acquired by machine learning systems which try to mimic common sense, as exhibited by humans, is inherently incomplete, redundant or even contradictory. Thus, the main characteristics of common sense is nonmonotonicity, which is introduced by exceptions to general rules, redundancy, which is introduced by continuous belief revisions and ambiguity, which is introduced ...

This is a position paper about the relations among artificial intelligence (AI), mathematical logic and the formalization of common-sense knowledge and reasoning. It also treats other problems of concern to both AI and philosophy. I thank the editor for inviting it. The position advocated is that philosophy can contribute to AI if it treats some of its traditional subject matter in more detail ...

This paper presents a scheduling method using hypothetical reasoning to achieve reliability in outage planning for electric power facilities. In general sense, hypothetical reasoning is a kind of non-monotonic reasoning with the ability to deal with incomplete knowledge, including a matter which cannot be verified. It consists of a problem solver and a TMS (Truth Maintenance System). We apply t...

We mathematically model Ignacio Matte Blanco’s principles of symmetric and asymmetric being through use of an ultrametric topology. We use for this the highly regarded 1975 book of this Chilean psychiatrist and pyschoanalyst (born 1908, died 1995). Such an ultrametric model corresponds to hierarchical clustering in the empirical data, e.g. text. We show how an ultrametric topology can be used a...

We show how to solve the classical ATP benchmark test problem Schu-bert's Steamroller, and other puzzles, in the nonclassical framework of extended disjunctive logic programming (EDLP) where neither Contrapo-sition nor Reasoning by Cases are valid principles of inference. While thèSteamroller' can be solved using only Detachment and Disjunctive Syl-logism, another puzzle, `Who killed aunt Agath...

We define the formal framework of r-hybrid knowledge bases (KBs) integrating ontologies and rules. A r-hybrid KB has a structural component (ontology) and a rule component. Such a framework is very general, in the sense that: (i) the construction is parametric with respect to the logic used to specify the structural component; (ii) the rule component is very expressive, since it consists of a D...

Good sense can be defined as the quality which someone has to make sensible decisions about what to do in specific situations. It can also be defined as good judgment. However, in order to have good sense, people have to use common sense knowledge. This is not different to computers. Nowadays, computers are still not able to make sensible decisions and one of the reasons is the fact that they l...

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed...

Most logic-based AI research works at a meta-theoretical level, producing new logics and studying their properties. Little effort is made to show how these logics can be used to formalise object-level theories of common sense. In the spirit of Pat Hayes’s Naive Physics Manifesto, the present paper supplies a formalisation of a non-trivial benchmark problem in common sense physical reasoning, na...