This paper is focused on use of state representation of behavior for agents using multicriterial decision making as their control mechanism. Use of this approach requires modifications in description of the problem and agent`s environment. One of possible ways to provide necessary information to an agent, to ensure it will perform its function correctly is to establish a state representation of...

The surge in cybercrime has emerged as a pressing concern contemporary society due to its far-reaching financial, social, and psychological repercussions on individuals. Beyond inflicting monetary losses, cyber-attacks exert adverse effects the social fabric well-being of affected In order mitigate deleterious consequences cyber threats, adoption an intelligent agent-based solution enhance spee...

Each agent (animal or human) perceives and reacts to its own environment according to its own psychophysical structure and organization. This is true for machine intelligence as well as for an agent. Machine intelligence must perceive and react to its environment according to its own cognitive organization, which requires a linguistic model. We claim that we need a logico-linguistic ontology fo...

Multi agent system has been one of the most challenging parts in the field of artificial intelligence. Multiple agents are applied to do definite works using own intelligence. Communication is a medium through which agents can contact each other and perform at their best. In this paper we have formed multi agent communicative rule based architecture algorithmically. The framework depicts how th...

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is rely...

We propose a new measure of intelligence for general reinforcement learning agents, based on the notion that an agent’s environment can change at any step of execution of the agent. That is, an agent is considered to be interacting with its environment in real-time. In this sense, the resulting intelligence measure is more general than the universal intelligence measure (Legg and Hutter, 2007) ...

Simulations are used extensively for studying artificial intelligence. However, the simulation technology in use by and designed for the artificial intelligence community often fails to take advantage of much of the work by the larger simulation community to produce distributed, repeatable, and efficient simulations. We present the new system known as System for Parallel Agent Discrete Event Si...

Human intelligence has evolved along with the use of more and more sophisticated tools, allowing Homo Faber (from Homo Habilis to Homo Sapiens Sapiens) to cope with environment changes, as well as to adapt the environment to his needs. Analogously, in this seminal paper we introduce the notion of Agens Faber, conveying the idea that agent intelligence should not be considered as separated by th...