Probabilistic Multiagent Reasoning over Annotated Amalgamated F-Logic Ontologies

In a multiagent system (MAS), agents can have different opinions about a given problem. In order to solve the problem collectively they have to reach consensus about the ontology of the problem. A solution to probabilistic reasoning in such an environment by using a social network of trust is given. It is shown that frame logic can be annotated and amalgamated by using this approach which gives a foundation for collective ontology development in MAS. Consider the following problem: a set of agents in a multiagent system (MAS) model a certain domain in order to collectively solve a problem. Their opinions about the domain differ in various ways. The agents are connected into a social network defined by trust relations. The problem to be solved is how to obtain consensus about the domain. 1. Introduction To formalize the problem let be a set of agents, let be a trust relation defined over , and let be a problem domain consisting of a set of objects. Let further be a set of all possible statements about , and let be a relation over . We will denote by the social ontology expressed by the agents. What is the probability that a certain statement from the expressed statements in is true? By modeling some domains of interest (using a formalism like ontologies, knowledge bases, or other models) a person expresses his/her knowledge about it. Thus the main concept of interest in modeling any domain is knowledge. Nonaka and Takeuchi once defined knowledge as a “justified true belief” [1] whereby this definition is usually credited to Plato. This means that the modeling person implicitly presumes that the expressed statements in his/her model are true. On the other hand if one asks the important question what is the truth?, we arrive at one of the fundamental philosophical questions. Nietzsche once argued in [2] that a person is unable to prove the truth of a statement which is nothing more than the invention of fixed conventions for merely practical purposes, like repose, security, and/or consistence. According to this view, no one can prove that this paper is not just a fantasy of the reader reading it. The previously outlined definition of knowledge includes, intentionally or not, two more crucial concepts: justified and belief. An individual will consider something to be true that he believes in, and, from that perspective, the overall truth will be a set of statements that the community believes in. This mutual belief makes this set of statements justified. The truth was once that the Earth was the center of the universe until philosophers and scientists