Research on quantum cognition in autonomous driving

Autonomous vehicles for the intention of human behavior of the estimated traffic participants and their interaction is the main problem in automatic driving system. Classical cognitive theory assumes that the behavior of human traffic participants is completely reasonable when studying estimation of intention and interaction. However, according to the quantum cognition and decision theory as well as practical traffic cases, human behavior including traffic behavior is often unreasonable, which violates classical cognition and decision theory. Based on the quantum cognitive theory, this paper studies the cognitive problem of pedestrian crossing. Through the case analysis, it is proved that the Quantum-like Bayesian (QLB) model can consider the reasonability of pedestrians when crossing the street compared with the classical probability model, being more consistent with the actual situation. The experiment of trajectory prediction proves that the QLB model can cover the edge events in interactive scenes compared with the data-driven Social-LSTM model, being more consistent with the real trajectory. This paper provides a new reference for the research on the cognitive problem of intention on bounded rational behavior of human traffic participants in autonomous driving.

Markov Decision Theory-Based Crowdsourcing Software Process Model

The word crowdsourcing, a compound contraction of crowd and outsourcing, was introduced by Jeff Howe in order to define outsourcing to the crowd. It is a sourcing model in which individuals or organizations obtain goods and services. These services include ideas and development of software or hardware, or any other business-task from a large, relatively open and often rapidly-evolving group of internet users; it divides work between participants to achieve a cumulative result. It has been used for completing various human intelligence tasks in the past, and this is an emerging form of outsourcing software development as it has the potential to significantly reduce the implementation cost. This chapter analyses the process of software development at a crowdsourced platform. The work analyses and identifies the phase wise deliverables in a competitive software development problem. It also proposes the use of Markov decision theory to model the dynamics of the development processes of a software by using a simulated example.

Optimal Decision-Making Model of Agricultural Product Information Based on Three-Way Decision Theory

As an effective heuristic method, three-way decision theory gives a new semantic interpretation to the three fields of the rough set, which has a huge application space. To classify the information of agricultural products more accurately under certain thresholds, this paper first makes a comprehensive evaluation of the decision, particularly the influence of the attributes of the event itself on the results and their interactions. By using fuzzy sets corresponding to membership and non-membership degree, this paper analyzes and puts forward two cases of proportional correlation coefficients in the transformation of a delayed decision domain, and selects the corresponding coefficients to compare the results directly. Finally, consumers can conveniently grasp product attribute information to make decisions. On this basis, this paper analyzed the standard data to verify the accuracy of the model. After that, the proposed algorithm, based on three decision-making agricultural product information classification processing, is applied to the relevant data of agricultural products. The experimental results showed that the algorithm can obtain more accurate results through a more straightforward calculation process. It can be concluded that the algorithm proposed in this paper can enable people to make more convenient and accurate decisions based on product attribute information.

Development of decision approval rules in multichannel decision-making systems

The research is devoted to the development of rules for the coordination of decisions in multichannel decision-making systems. Systems are considered that in an automated continuous mode process incoming signals from different channels and, on their basis, make the final decision. One of the most problematic stages in the operation of such systems is their own coordination of solutions received from different channels. There may be cases where different channels provide signals with opposite values. Then the choice of the decisive solution should depend on the reliability of the channels under consideration. The object of research is the processes that take place during the coordination of decisions in multichannel decision-making systems. The development and implementation of such systems will allow in an automated mode to generalize the solution obtained through different channels, to increase the reliability and efficiency of the systems as a whole. During the study, the following methods were used: – a systematic approach – when analyzing the structure and functioning of multichannel one-stage decision-making systems; – method of mathematical modeling – for formalizing the problem of coordinating decisions in multichannel decision-making systems; – method of analysis – when developing rules for agreeing decisions. The authors analyzed the structure of a one-stage multichannel decision-making system. The case is considered when the channels, based on the initial data entering the system, decide on the presence or absence of a certain fact. That is, the channels send signals from the set {True, False}. In the study, decision rules for the coordination of decisions were developed, taking into account not only the signals received from different channels, but also the reliability of the channels themselves. As is usual in decision theory, different rules can give different results for the same initial data. The choice of the decision rule depends on the decision maker, its personal psychological qualities and the scope of the system.