Abstract:
Crowdsourcing is a model where individuals or organizations receive
services from a large group of Internet users including ideas, finances,
completing a complex task, etc. Several crowdsourcing websites have failed due
to la
ck of user participation; hence, the success of crowdsourcing platforms is
manifested by the mass of user participation. However, an issue of motivating
users to participate in crowdsourcing platform stays challenging. We have
proposed a new approach, i.e.
, reinforcement learning
-
based gamification
method to motivate users. Gamification has been a practical approach to
engaging users in many fields, but still, it needs an improvement in the
Crowdsourcing platform. In this paper, the gamification approach is
strengthened
by a reinforcement learning algorithm. We have created an intelligent agent
using the Reinforcement learning algorithm (Q
-
learning). This agent suggests an
optimal action plan that yields maximum reward points to the users for their
active pa
rticipation in the Crowdsourcing application. Also, its performance is
compared with the SARSA algorithm (On
-
policy learning), which is another
Reinforcement learning algorithm.