Entity

Time filter

Source Type


Plikynas D.,Kazimieras Simonavicius University
WSEAS Transactions on Systems | Year: 2014

This multidisciplinary paper starts from a review of a wide range of theories across various disciplines in search of common field-like fundamental principles of coordination and self-organization existing on the quantum, cellular, and social levels. These studies outline universal principles, which are further employed to formulate main premises and postulates for the proposed OSIMAS (oscillation-based multi-agent system) simulation paradigm. OSIMAS design is based on neuroscience discoveries about the oscillating nature of the agents mind states and of the nonlocal field-like self-organization properties of modern information societies. OSIMAS approach considers conceptual trinity of the core models. In this paper there is presented the pervasive information field conceptual model in more details. In this way, the paper sheds new light on social systems in terms of fundamental properties of information and order. We also provide a review of some related other studies and applications of virtual field-based modeling. Source


Plikynas D.,Kazimieras Simonavicius University
NeuroQuantology | Year: 2015

Enabled by recent neuroscience and especially electroencephalogram (EEG) studies, this paper describes a conceptually novel modeling approach, based on quantum theory, to basic human mind states as systems of coherent oscillation. The aim is to bridge the gap between fundamental theory, experimental observation and the simulation of agents’ mind states. The proposed approach, i.e., an oscillating agent model (OAM), reveals possibilities of employing wave functions and quantum operators for a stylized description of basic mind states and the transitions between them. In the OAM the basic mind states are defined using experimentally observed EEG spectra, i.e., brainwaves (delta, theta, alpha, beta and gamma), which reveal an oscillatory nature of agents’ mind states. Such an approach provides an opportunity to model the dynamics of basic mind states by employing stylized oscillation-based representations of the characteristic EEG power spectral density (PSD) distributions of brainwaves observed in experiments. In other words, the proposed OAM describes a probabilistic mechanism for transitions between basic mind states characterized by unique sets of brainwaves. The instantiated theoretical framework is pertinent not only for the simulation of the individual cognitive and behavioral patterns observed in experiments, but also for the prospective development of OAM-based multi-agent systems. © 2015, NeuroQuantology. All rights reserved. Source


Grant
Agency: Cordis | Branch: FP7 | Program: CP-IP | Phase: SSH.2013.3.2-1 | Award Amount: 6.25M | Year: 2014

SI-DRIVE extends knowledge about social innovation (SI) in three major directions: - Integrating theories and research methodologies to advance understanding of SI leading to a comprehensive new paradigm of innovation. - Undertaking European and global mapping of SI, thereby addressing different social, economic, cultural, historical and religious contexts in eight major world regions. - Ensuring relevance for policy makers and practitioners through in-depth analyses and case studies in seven policy fields, with cross European and world region comparisons, foresight and policy round tables. SI-DRIVE involves 15 partners from 12 EU Member States and 10 from other parts of the world. The approach adopted carefully interlinks the research process to both the complexity of the topic and the project workflow. First, cyclical iteration between theory development, methodological improvements, and policy recommendations. Second, two mapping exercises at European and global level. Initial mapping will capture basic information about 1000\ actual successful and failed social innovations from a wide variety of sources worldwide, leading to a typology of SI (testing the SI perspectives proposed by the BEPA report) and using this to examine the global SI distribution. Subsequent mapping will use the typology to focus on well documented SI, leading to the selection of 10 cases each for in-depth analysis in the seven SI-DRIVE Policy Fields. Third, these case studies will be further analysed, used in stakeholder dialogues in 7 policy field platforms and in analysis of cross-cutting dimensions (e.g. gender, diversity, ICT), carefully taking into account cross-sector relevance (private, public, civil sectors), and future impact. The outcomes of SI-DRIVE will address all objectives required by the Call, cover a broad range of research dimensions, impacting particularly in terms of changing society and empowerment, and contributing to the objectives of the Europe 2020 Strategy.


Plikynas D.,Kazimieras Simonavicius University | Raudys A.,Kazimieras Simonavicius University | Raudys S.,Vilnius University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

This paper investigates regularities in excitation information propagation in social interaction. We use cellular automaton approach where it is assumed that social media is composed from tens of thousands of community agents. Each agent can transmit and get a signal from several nearest neighbours. Weighted sums of input signals after reaction delay are transmitted to the closest agents. The model's originality consists in the exploitation of neuron-based agent schema with nonlinear activation function employed to determine the reaction delay, the agent recovery period, and algorithms that define cooperation of several excitable groups. In the grouped model, each agent group can send its excitation signal to other groups. The agents and their groups should acquire diverse media parameters of social media in order to ensure desirable for social media character of excitation wave propagation patterns. The novel media model allows methodical analysis of propagation of several competing novelty signals. Simulations are very fast and can be useful for understanding and control of the simulated human and agent-based social mediums, planning and performing social and economy research. © 2014 Springer International Publishing Switzerland. Source


Plikynas D.,Kazimieras Simonavicius University | Raudys A.,Kazimieras Simonavicius University | Raudys S.,Vilnius University
Journal of Experimental and Theoretical Artificial Intelligence | Year: 2015

This paper investigates excitation information propagation in artificial societies. We use a cellular automaton approach, in which it is assumed that social media is composed of tens of thousands of community agents, where useful (innovative) information can be transmitted to the closest neighbouring agents. The model's originality consists of the exploitation of artificial neuron-based agent schema with a nonlinear activation function to determine the reaction delay, the refractory (agent recovery) period and algorithms that define mutual cooperation among several excitable groups that comprise the agent population. In the grouped model, each agent group can send its excitation signal to the leaders of the groups. The novel media model allows a methodical analysis of the propagation of several competing innovation signals. The simulations are very fast and can be useful for understanding and controlling excitation propagation in social media, planning, and social and economic research. © 2014 Taylor and Francis. Source

Discover hidden collaborations