Using the Myers-Briggs Type Indicator (MBTI) for Modeling Multiagent Systems

The formation of high-performance teams has been a constant challenge for organizations, which despite considering human capital as one of the most important resources, it still lacks the means to allow them to have a better understanding of several factors that influence the formation of these teams. In this sense, studies also demonstrate that teamwork has a significant impact on the results presented by organizations, in which human behavior is highlighted as one of the main aspects to be considered in the building of work teams. The Myers-Briggs Type Indicator seeks to classify the behavioral preferences of individuals around eight characteristics, which grouped as dichotomies, describe different psychological types. With it, researchers have sought to expand the ability to understand the human factor, using strategies with multiagent systems that, through experiments and simulations, using computer resources, enable the development of artificial agents that simulate human actions. In this work, we present an overview of the research approaches that use MBTI to model agents, aiming at providing a better knowledge of human behavior. Additionally, we make a preliminary discussion of how these results could be explored in order to advance the studies of psychological factors' influence in organizations' work teams formation.

The Consensus of Different Fractional-Order Chaotic Multiagent Systems Using Adaptive Protocols

This paper is concerned with the adaptive consensus problem of incommensurate chaotic fractional order multiagent systems. Firstly, we introduce fractional-order derivative in the sense of Caputo and the classical stability theorem of linear fractional order systems; also, algebraic graph theory and sufficient conditions are presented to ensure the consensus for fractional multiagent systems. Furthermore, adaptive protocols of each agent using local information are designed and a detailed analysis of the leader-following consensus is presented. Finally, some numerical simulation examples are also given to show the effectiveness of the proposed results.

Relative controllability of multiagent systems with pairwise different delays in states

In this manuscript, relative controllability of leader–follower multiagent systems with pairwise different delays in states and fixed interaction topology is considered. The interaction topology of the group of agents is modeled by a directed graph. The agents with unidirectional information flows are selected as leaders, and the others are followers. Dynamics of each follower obeys a generic time-invariant delay differential equation, and the delays of agents, which satisfy a specified condition, are different one another because of the degeneration or burn-in of sensors. With a neighbor-based protocol steering, the dynamics of followers become a compact form with multiple delays. Solution of the multidelayed system without pairwise matrices permutation is obtained by improving the method in the references, and relative controllability is established via Gramian criterion. Further rank criterion of a single delay system is dealt with. Simulation illustrates the theoretical deduction.