RULER (Relative Universal LLM-Elicited Rewards) eliminates the need for hand-crafted reward functions by using an LLM-as-judge to automatically score agent trajectories. Simply define your task in the ...
Reinforcement Learning Solutions to Stochastic Multi-Agent Graphical Games With Multiplicative Noise
Abstract: This paper investigates reinforcement learning algorithms for discrete-time stochastic multi-agent graphical games with multiplicative noise. The Bellman optimality equation for stochastic ...
Abstract: The Vehicle Routing Problem with Multiple Soft Time Windows (VRPMSTW) is a challenging combinatorial optimization problem where a fleet of vehicles must deliver goods to a set of customers, ...
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