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Authors: Shikhar Raje 1 ; Navjyoti Singh 1 and Shobhit Mohan 2

Affiliations: 1 International Institute of Information Technology and Hyderabad, India ; 2 Hyderabad Central University, India

ISBN: 978-989-758-201-1

Keyword(s): Preference Aggregation, Stochastic Modelling, Dynamic Voting, Markov Decision Processes, Computational Complexity, Algorithm Analysis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Co-Evolution and Collective Behavior ; Computational Intelligence ; Enterprise Information Systems ; Evolutionary Computing ; Evolutionary Multiobjective Optimization ; Game Theory Applications ; Representation Techniques ; Soft Computing

Abstract: Markov Decision Processes (MDPs) and their variants are standard models in various domains of Artificial Intelligence. However, each model captures a different aspect of real-world phenomena and results in different kinds of computational complexity. Also, MDPs are recently finding use in the scenarios involving aggregation of preferences (such as recommendation systems, e-commerce platforms, etc.). In this paper, we extend one such MDP variant to explore the effect of including observations made by stochastic agents, on the complexity of computing optimal outcomes for voting results. The resulting model captures phenomena of a greater complexity than current models, while being closer to a real world setting. The utility of the theoretical model is demonstrated by application to the real world setting of crowdsourcing. We address a key question in the crowdsourcing domain, namely, the Exploration Vs. Exploitation problem, and demonstrate the flexibility of adaptation of MDP-based m odels in Dynamic Voting scenarios. (More)

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Paper citation in several formats:
Raje, S.; Singh, N. and Mohan, S. (2016). Modelling Evolving Voting Behaviour on Internet Platforms - Stochastic Modelling Approaches for Dynamic Voting Systems.In Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016) ISBN 978-989-758-201-1, pages 239-244. DOI: 10.5220/0006073502390244

@conference{ecta16,
author={Shikhar Raje. and Navjyoti Singh. and Shobhit Mohan.},
title={Modelling Evolving Voting Behaviour on Internet Platforms - Stochastic Modelling Approaches for Dynamic Voting Systems},
booktitle={Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016)},
year={2016},
pages={239-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006073502390244},
isbn={978-989-758-201-1},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2016)
TI - Modelling Evolving Voting Behaviour on Internet Platforms - Stochastic Modelling Approaches for Dynamic Voting Systems
SN - 978-989-758-201-1
AU - Raje, S.
AU - Singh, N.
AU - Mohan, S.
PY - 2016
SP - 239
EP - 244
DO - 10.5220/0006073502390244

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