This paper discusses questions about communication of probabilistic knowledge in the light of current theories of agent communication. It will argue that there is a semantic gap between these theories and research areas related to probabilistic knowledge representation and communication,…

In systems where agents are required to interact with a partially known and dynamic world, sensors can be used to obtain further knowledge about the environment. However, sensors may be unreliable, that is, they may deliver wrong information (due, e.g.,…

Over the last several years, multidimensional data modeling has had several proposals for its formalisation; on the other hand, the incorporation of fuzzy logic in databases has increased the need to represent uncertainty.
However, to our knowledge, so far projects…

The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both…

Fish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able…

There are three kinds of uncertainty in the process of fish-disease diagnosis, such as randomicity, fuzzy and imperfection, which affect the veracity of fish-disease diagnostic conclusion. So, it is important to construct a fish-disease diagnostic model to effectively deal with…

Current reasoning systems attempt to model an agent's knowledge and interaction with its environment in a symbolic manner. This environment, its world is generally dynamic and changing due to natural evolution or the actions of other agents that are a…

The production of educational contents in academic environments has been traditionally developed without an integral plan which allows their adequate distribution and access. In addition, it produces effort duplication and misuse of resources. As a possible solution, this work proposes…

Defeasible Logic Programming (DeLP) is an extension of Logic Programming capturing common-sense reasoning features. The DeLP language can manage defeasible reasoning, allowing the representation of defeasible and non- defeasible knowledge. Since DeLP syntax is based on a PROLOG-like notation, the…

Negative information can be represented in several classes of logic programs. These approaches were first motivated by the search for an appropriate declarative semantics for negation as failure. Recently, some formalizations of monotonic negation were also introduced in logic programming…