This paper extends the link between evolutionary game theory and multi-agent reinforcement learning to multistate games. In previous work, we introduced piecewise replicator dynam...
Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique, which can be used to find an optimal, or near optimal, solution to a numerical and quali...
Stochastic Shortest Path problems (SSPs) can be efficiently dealt with by the Real-Time Dynamic Programming algorithm (RTDP). Yet, RTDP requires that a goal state is always reach...
Abstract. We propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time...
Stochastic Flow Models (SFMs) are stochastic ystems that abstract the dynamics of complex discrete event systems involving the control of sharable resources. SFMs have been used to...