Abstract. For large state-space Markovian Decision Problems MonteCarlo planning is one of the few viable approaches to find near-optimal solutions. In this paper we introduce a new...
In this paper we introduce a generalization of Paging to the case where there are many threads of requests. This models situations in which the requests come from more than one ind...
Esteban Feuerstein, Alejandro Strejilevich de Loma
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
To address coordination and complexity issues, we formulate a grid task allocation problem as a bargaining based self-adaptive auction and propose the BarSAA grid task-bundle alloc...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...