EMERGING THE EMERGENCE SOCIOLOGY: The Philosophical Framework of Agent-Based Social Studies

The structuration theory originally provided by Anthony Giddens and the advance improvement of the theory has been trying to solve the dilemma came up in the epistemological aspects of the social sciences and humanity. Social scientists apparently have to choose whether they are too sociological or too psychological. Nonetheless, in the works of the classical sociologist, Emile Durkheim, this thing has been stated long time ago. The usage of some models to construct the bottom-up theories has followed the vast of computational technology. This model is well known as the agent based modeling. This paper is giving a philosophical perspective of the agent-based social sciences, as the sociology to cope the emergent factors coming up in the sociological analysis. The framework is made by using the artificial neural network model to show how the emergent phenomena came from the complex system. Understanding the society has self-organizing (autopoietic) properties, the Kohonen’s self-organizing map is used in the paper. By the simulation examples, it can be seen obviously that the emergent phenomena in social system are seen by the sociologist apart from the qualitative framework on the atomistic sociology. In the end of the paper, it is clear that the emergence sociology is needed for sharpening the sociological analysis in the emergence sociology

Situation Modeling of Regional Development in the Republic of Kazakhstan

The methodology of situation modeling was based on the application of fuzzy cognitive maps, indistinct regional data and indistinct time horizon. Based on indistinct number of involved concepts, the model enables users to create their own situations with fuzzy quantity of available concepts including both the existing and the added ones. The added concepts are characterized by the set properties and database related to no less than three fuzzy time horizons. The number of set impulses is fuzzy as well. Cognitive map training was based on the artificial intelligence element – the active Hebb learning rule. The impact of concepts was defined in the course of training. Fine adjustment of the fuzzy cognitive map was achieved by changing the training order using a rank scale and Saati’s sorting algorithm. The developed computer software was used in simulation modeling of regional socio-economic processes related to the project aiming at tourism development of the Alacol Lake in Almaty region. Research results are shown in the form of a fuzzy cognitive map reflecting internal and external relations within the region, graphs reflecting socio-economic development and the Bossel criterion. Simulation of allocations had a positive effect: GRP (Gross Regional Product) growth along with increase in employment and environmental improvement. The proposed approach provides a tool for forecasting of regional development and solution of different regional problems. This approach can be used with regard to any administrative-territorial entity, provided relevant statistical data

Situation Modeling of Regional Development in the Republic of Kazakhstan

The methodology of situation modeling was based on the application of fuzzy cognitive maps, indistinct regional data and indistinct time horizon. Based on indistinct number of involved concepts, the model enables users to create their own situations with fuzzy quantity of available concepts including both the existing and the added ones. The added concepts are characterized by the set properties and database related to no less than three fuzzy time horizons. The number of set impulses is fuzzy as well. Cognitive map training was based on the artificial intelligence element – the active Hebb learning rule. The impact of concepts was defined in the course of training. Fine adjustment of the fuzzy cognitive map was achieved by changing the training order using a rank scale and Saati’s sorting algorithm. The developed computer software was used in simulation modeling of regional socio-economic processes related to the project aiming at tourism development of the Alacol Lake in Almaty region. Research results are shown in the form of a fuzzy cognitive map reflecting internal and external relations within the region, graphs reflecting socio-economic development and the Bossel criterion. Simulation of allocations had a positive effect: GRP (Gross Regional Product) growth along with increase in employment and environmental improvement. The proposed approach provides a tool for forecasting of regional development and solution of different regional problems. This approach can be used with regard to any administrative-territorial entity, provided relevant statistical data

Human Factors in Agile Software Development

Through our four years experiments on students' Scrum based agile software development (ASD) process, we have gained deep understanding into the human factors of agile methodology. We designed an agile project management tool - the HASE collaboration development platform to support more than 400 students self-organized into 80 teams to practice ASD. In this thesis, Based on our experiments, simulations and analysis, we contributed a series of solutions and insights in this researches, including 1) a Goal Net based method to enhance goal and requirement management for ASD process, 2) a novel Simple Multi-Agent Real-Time (SMART) approach to enhance intelligent task allocation for ASD process, 3) a Fuzzy Cognitive Maps (FCMs) based method to enhance emotion and morale management for ASD process, 4) the first large scale in-depth empirical insights on human factors in ASD process which have not yet been well studied by existing research, and 5) the first to identify ASD process as a human-computation system that exploit human efforts to perform tasks that computers are not good at solving. On the other hand, computers can assist human decision making in the ASD process.Comment: Book Draf

Speaker Normalization Using Cortical Strip Maps: A Neural Model for Steady State vowel Categorization

Auditory signals of speech are speaker-dependent, but representations of language meaning are speaker-independent. The transformation from speaker-dependent to speaker-independent language representations enables speech to be learned and understood from different speakers. A neural model is presented that performs speaker normalization to generate a pitch-independent representation of speech sounds, while also preserving information about speaker identity. This speaker-invariant representation is categorized into unitized speech items, which input to sequential working memories whose distributed patterns can be categorized, or chunked, into syllable and word representations. The proposed model fits into an emerging model of auditory streaming and speech categorization. The auditory streaming and speaker normalization parts of the model both use multiple strip representations and asymmetric competitive circuits, thereby suggesting that these two circuits arose from similar neural designs. The normalized speech items are rapidly categorized and stably remembered by Adaptive Resonance Theory circuits. Simulations use synthesized steady-state vowels from the Peterson and Barney [J. Acoust. Soc. Am. 24, 175-184 (1952)] vowel database and achieve accuracy rates similar to those achieved by human listeners. These results are compared to behavioral data and other speaker normalization models.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model

This paper presents an individual-based predator-prey model with, for the first time, each agent behavior being modeled by a Fuzzy Cognitive Map (FCM), allowing the evolution of the agent behavior through the epochs of the simulation. The FCM enables the agent to evaluate its environment (e.g., distance to predator/prey, distance to potential breeding partner, distance to food, energy level), its internal state (e.g., fear, hunger, curiosity) with memory and choosing several possible actions such as evasion, eating or breeding. The FCM of each individual is unique and is the outcome of the evolution process throughout the simulation. The notion of species is also implemented in a way that species emerge from the evolving population of agents. To our knowledge, our system is the only one that allows modeling the links between behavior patterns and speciation. The simulation produces a lot of data including: number of individuals, level of energy by individual, choice of action, age of the individuals, average FCM associated to each species, number of species. This study investigates patterns of macroevolutionary processes such as the emergence of species in a simulated ecosystem and proposes a general framework for the study of specific ecological problems such as invasive species and species diversity patterns. We present promising results showing coherent behaviors of the whole simulation with the emergence of strong correlation patterns also observed in existing ecosystems

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications