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A Primal Decomposition Approach to Globally Coupled Aggregative Optimization over Networks
We consider a class of multi-agent optimization problems, where each agent has a local objective function that depends on its own decision variables and the aggregate of others, and is willing to cooperate with other agents to minimize the sum of the local objectives.
Distributed Computation of Stochastic GNE with Partial Information: An Augmented Best-Response Approach
In this paper, we focus on the stochastic generalized Nash equilibrium problem (SGNEP) which is an important and widely-used model in many different fields.
Simulation Studies on Deep Reinforcement Learning for Building Control with Human Interaction
The building sector consumes the largest energy in the world, and there have been considerable research interests in energy consumption and comfort management of buildings.
A Discrete-Time Switching System Analysis of Q-learning
Based on these two systems, we derive a new finite-time error bound of asynchronous Q-learning when a constant stepsize is used.
