Reinaldo Augusto da Costa Bianchi

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This article presents two new algorithms for finding the optimal solution of a Multi-agent Multi-objective Reinforcement Learning problem. Both algorithms make use of the concepts of modularization and acceleration by a heuristic function applied in standard Reinforcement Learning algorithms to simplify and speed up the learning process of an agent that(More)
The Keystroke-Level Model (KLM) is an interface evaluation method that use as metric the time needed to perform an executed action to complete a given task. The description used in KLM is very similar to the formalism that Markov Decision Process (MDP) uses to describe a domain, in which an artificial agent must perform a sequence of actions in order to(More)
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