4 papers
Quantum-Inspired Reinforcement Learning in the Presence of Epistemic Ambivalence
Alireza Habibi, Saeed Ghoorchian, Setareh Maghsudi
The complexity of online decision-making under uncertainty stems from the requirement of finding a balance between exploiting known strategies and exploring new possibilities. Natu…
Online Learning with Costly Features in Non-stationary Environments
Saeed Ghoorchian, Evgenii Kortukov, Setareh Maghsudi
Maximizing long-term rewards is the primary goal in sequential decision-making problems. The majority of existing methods assume that side information is freely available, enabling…
Non-stationary Delayed Combinatorial Semi-Bandit with Causally Related Rewards
Saeed Ghoorchian, Setareh Maghsudi
Sequential decision-making under uncertainty is often associated with long feedback delays. Such delays degrade the performance of the learning agent in identifying a subset of arm…
Multi-Armed Bandit for Energy-Efficient and Delay-Sensitive Edge Computing in Dynamic Networks with Uncertainty
Saeed Ghoorchian, Setareh Maghsudi
In the edge computing paradigm, mobile devices offload the computational tasks to an edge server by routing the required data over the wireless network. The full potential of edge…