6 citations · 7 across the 8 of their papers we have counts for
8 papers
Risk Sensitivity in Markov Games and Multi-Agent Reinforcement Learning: A Systematic Review
Hafez Ghaemi, Shirin Jamshidi, Mohammad Mashreghi +2
Markov games (MGs) and multi-agent reinforcement learning (MARL) are studied to model decision making in multi-agent systems. Traditionally, the objective in MG and MARL has been r…
Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games
Hafez Ghaemi, Hamed Kebriaei, Alireza Ramezani Moghaddam +1
Classical multi-agent reinforcement learning (MARL) assumes risk neutrality and complete objectivity for agents. However, in settings where agents need to consider or model human e…
A Consensus-Based Generalized Multi-Population Aggregative Game with Application to Charging Coordination of Electric Vehicles
Mahsa Ghavami, Babak Ghaffarzadeh Bakhshayesh, Mohammad Haeri +2
This paper introduces a consensus-based generalized multi-population aggregative game coordination approach with application to electric vehicles charging under transmission line c…
Generalized Stochastic Dynamic Aggregative Game for Demand-Side Management in Microgrids with Shared Battery
Shahram Yadollahi, Hamed Kebriaei, Sadegh Soudjani
In this paper, we focus on modeling and analysis of demand-side management in a microgrid where agents utilize grid energy and a shared battery charged by renewable energy sources.…
Learning Robust Model Predictive Control for Voltage Control of Islanded Microgrid
Sahand Kiani, Hamed Kebriaei, Mohsen Hamzeh +1
This paper proposes a novel control design for voltage tracking of an islanded AC microgrid in the presence of {nonlinear} loads and parametric uncertainties at the primary level o…
Continuous Reinforcement Learning-based Dynamic Difficulty Adjustment in a Visual Working Memory Game
Masoud Rahimi, Hadi Moradi, Abdol-hossein Vahabie +1
Dynamic Difficulty Adjustment (DDA) is a viable approach to enhance a player's experience in video games. Recently, Reinforcement Learning (RL) methods have been employed for DDA i…