Recent reinforcement learning (RL) methods have achieved success in various domains. However, multi-agent RL (MARL) remains a challenge in terms of decentralization, partial …
Adaptive incentives are a valuable tool shown to improve the efficiency of complex multiagent systems and could produce win-win situations for all stakeholders. However, their …
Recent reinforcement learning (RL) methods have achieved success in various domains. However, multi-agent RL (MARL) remains a challenge in terms of decentralization, partial …
Adaptive incentives are a valuable tool shown to improve the efficiency of complex multiagent systems and could produce win-win situations for all stakeholders. However, their …
In this dissertation, we discuss the mathematically rigorous multi-agent reinforcement learning frameworks of mean field games (MFG) and mean field control (MFC). Dynamical …