Агрессия в мире аниматов, или О некоторых механизмах управления агрессивным поведением в групповой робототехнике
Some possible ways of implementing aggression as one of the mechanisms for the social behavior formation in robots groups are discussed in this work. Aggression is considered as a way to resolve conflicts over resources. The features of the aggressive behavior of eusocial insects (ants) are used as basic. A reactive model of behavior was proposed. The aggressive component is integrated into the demand-emotional architecture of the animat's control system, which is presented as a hybrid neuroproduction system. Also, the question of using an aggressive component at the phenomenological level of behavior management. Imitation modeling experiments were carried out on the example of realization of domination in a group. The issue of determining the basic mechanisms for feed areas distribution, which is part of the foraging task, is also considered. It is shown that such mechanisms are domination (as the result of aggressive actions) and the animats memory. The simulation results confirm that the addition of the "aggressiveness" parameter to the control system provides a variety of animats behavior taking into account the environment state. The proposed model of aggressive behavior does not depend on the task, which is solved, and allows to manage the group in natural form.
Possible methods of implementing aggression as one of the mechanisms in the formation of social behavior in groups of robots are discussed. Aggression is seen as a way to resolve conflicts over resources. The features of the aggressive behavior of eusocial insects (ants) are used as a basis. The aggressive component is integrated into the need-emotional architecture of the robot control system, which is presented as a hybrid neuro-production system. The proposed mechanism can be used as a base for implementing various models of social behavior in group robotics.
Bayesian Belief Networks (BBN) provide a comprehensible framework for representing complex systems that allows including expert knowledge and statistical data simultaneously. We explored BBN models for estimating risky behavior rate and compared several network structures, both expert-based and data-based. To learn and evaluate models we used generated behavior data with 9393 observations. We applied both score-based and constraint-based structure learning algorithms. The score-based structures represented better quality scores according to BIC and log-likelihood, prediction quality was almost the same for databased models and lower but sufficient for expert-based models. Hence, in case of limited data we can reduce computations and apply expert-based structure for solving practical issues.
The key regulator in the control of aggressive behavior is dopamine receptors. Association of variants in these genes with aggression has been shown in modern populations. However, these studies have not been conducted in traditional cultures. The aim of our study was to investigate population features in distributions of allele and genotype frequencies of DRD2 rs1800497, DRD4 120 bp Ins, and DRD4 exon III polymorphisms and their associations with aggressive behavior in the traditional African populations of Hadza and Datoga, which display a contrast in their culturally permitted aggression. Overall, 820 healthy unrelated Hadza and Datoga individuals were studied. Self‐rated scores of aggression were collected using Buss and Perry's Aggression Questionnaire. Polymerase chain reaction‐Restriction fragment length polymorphism (PCR‐RFLP) was used to determine the genotype of each individual. We show that the Hadza and the Datoga differed significantly in allele and genotype frequencies of all studied loci. Our association analysis detected that only ethnicity and sex of individuals significantly influenced their aggression rank, but we failed to identify any associations of DRD2 rs1800497, DRD4 120 bp Ins, or DRD4 exon III polymorphisms with aggression. Thus, our data have no strong evidence to support the involvement of polymorphisms of DRD2 and DRD4 in controlling aggressive behavior.
This paper discusses a problem of distributed data processing in mobile robot’s group. The robot’s group is typified as a static swarm. Static swarm is a model, which is characterized by the absence of a control сenter and is represented by the network with fixed topology at some time interval which consists of locally interacting agents. The main features that distinguish the robot’s group general database from the classic distributed database are described. It is shown that the database does not require the global data dictionary storing information about the location of the database fragments. The data structure on each node is the same and can be described in the reference table. This table is loaded into robot’s memory when robot is initialized and, in fact, is the data dictionary. This database does not require distributed transactions, because data is written in the general database locally. The approach of logical queries organization in general database is offered. Definitions of imprecise and inconsistent data conformably to data which robots in the group are exchanging with are given. The approach of processing imprecise and inconsistent data which come to robot is proposed. This approach is based on elements of multisets theory, fuzzy sets theory and on evaluation of data reliability degree. The reliability degree is based on the experience of the previous data exchanges between robots. An important feature of the proposed method of imprecise and inconsistent data processing is that it is computationally simple and does not require much memory to store auxiliary information.
One of the widespread approaches to the issues of control in the group robotics is application of the social behavior models in the groups of robots. In this paper the author proposes to use this approach to fulfill the tasks of foraging. As a role model a Formicidae ant is proposed. This task is considered as a combination of three stages: finding food, returning to the ant hill and repeating the way to the place where food was found. It was proven that in order to come back home and repeatedly walk the way the Formicidae ants were navigated predominantly by the visual means using vector navigation (path integration) and landmark-guidance mechanisms. The basis of the proposed method is formed by the principles of memorizing the way by the visual landmarks and fuzzy control. The model of describing the way is introduced to the robot, which can define colors of the landmarks and approximately sense the direction to the landmark in respect to itself. A pattern for formation of a succinct way description was created, with the help of which the scout robot memorizes the way to the “food”. Certain regulations were developed, which let the follower robot transfer from the description of the route to the actions of its reproduction and in many ways copy an ant’s behavior. The actions are presented as elementary behavioral procedures, and each behavioral procedure is realized as a finite state automata. The results of the simulation modeling, which was conducted with the help of the framework of ROS based modeling system, are presented. Experiments were conducted in polygons with barriers and without them, with regular and irregular placing of the landmarks. As a quality criterion for the proposed method the author offers to consider a successful passing of the route by the follower robot, and this indicator in different series of experiments varies from 92 up to 98 %. The proposed method does not require robot’s great computation capacity and advanced sensory abilities. The developed method can also be applied to the tasks of reconnaissance and patrolling.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.