We study an interesting variant of the stochastic multi-armed bandit problem, which we call
the Fair-MAB problem, where, in addition to the objective of maximizing the sum of expected …

There are numerous situations when a service requester wishes to expertsource a series of
identical but non-trivial tasks from a pool of experts so as to achieve an assured accuracy …

Conventional path-planning strategies for GMA-WAAM may encounter challenges related to
geometrical features when printing complex-shaped builds. One alternative to mitigate …

Stochastic multi-armed bandit (MAB) mechanisms are widely used in sponsored search
auctions, crowdsourcing, online procurement, etc. Existing stochastic MAB mechanisms with …

We explore the class of problems where a central planner needs to select a subset of
agents, each with different quality and cost. The planner wants to maximize its utility while …

This thesis systematically explored the implementation of a Space-Filling strategy for an
artificially intelligent trajectory planning to be used in Wire Arc Additive Manufacturing …

Online learning problems are among the most abundant machine learning problems, such
as advertisement selection, movie recommendation, and node or link prediction in evolving …

Stochastic multi-armed bandit (MAB) mechanisms are widely used in sponsored search
auctions, crowdsourcing, online procurement, etc. Existing stochastic MAB mechanisms with …