Browsing by Author "Ashok K. Gupta"

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Agent based models of social systems and collective intelligence
(2009) Vivek Kumar Singh; Ashok K. Gupta
Agent-based modeling and simulation techniques have now become a suitable and popularly used approach to build useful models of social systems, which not only helps to get better understanding of various social phenomena but also enriches the agent-based computing paradigm in return. Agent-based models allow simulating social units such as individuals, households, organizations or nations and their direct or indirect interactions. These models demonstrate how global order and collective intelligence can emerge from relatively simple local interactions and can explain the dynamics of the emergent behaviour. The Agent-based modeling approach has provided the bridging link between psychological & sociological analysis of individual and social behaviours respectively, which was otherwise missing. This generative, proof-by- construction approach has also complemented the individual-centered research in cognitive science by showing that individual alone is not the crucial unit of cognition but is affected by environment and society besides affecting them as well. In this paper, we have given an analytical account of Agent-based modeling of emergent collective social behaviours, on these lines, along with relevant theoretical & experimental outcomes and their implications for multi-agent systems. ©2009 IEEE.
Agent-based computational modeling of emergent collective intelligence
(Springer Verlag, 2009) Vivek Kumar Singh; Divya Gautam; Rishi Raj Singh; Ashok K. Gupta
Collective Intelligence is a form of intelligence which emerges out of collaboration and coordination of many individual agents. A group of actors performing simple behaviours and interacting with fellow group members & the environment often produce global behaviours which seems intelligent. Understanding the emergence of intelligent collective behaviours in social systems, such as norms & conventions, higher level organizations, collective wisdom and evolution of culture from simple and predictable local interactions; has been an important research question since decades. Agent-based modeling of complex social behaviours by simulating social units as agents and modeling their interactions; provides a new generative approach to understanding the dynamics of emergence of collective intelligence behaviours. In this paper, we have presented an analytical account of nature, form and dynamics of collective intelligence, followed by some of our experimental work on evolution of collective intelligence. The paper concludes with a short discussion of the results and relevant implications for designing systems for achieving desired collective intelligence. © 2009 Springer Berlin Heidelberg.