Search Results for author: Pedro P. Santos

Found 3 papers, 1 papers with code

Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning

1 code implementation12 Oct 2022 Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo

We introduce hybrid execution in multi-agent reinforcement learning (MARL), a new paradigm in which agents aim to successfully perform cooperative tasks with any communication level at execution time by taking advantage of information-sharing among the agents.

Multi-agent Reinforcement Learning reinforcement-learning +1

Understanding the Impact of Data Distribution on Q-learning with Function Approximation

no code implementations23 Nov 2021 Pedro P. Santos, Francisco S. Melo, Alberto Sardinha, Diogo S. Carvalho

Second, we provide a novel four-state MDP that highlights the impact of the data distribution in the performance of a Q-learning algorithm with function approximation, both in online and offline settings.

Q-Learning

A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllers

no code implementations24 Jan 2021 Guilherme S. Varela, Pedro P. Santos, Alberto Sardinha, Francisco S. Melo

Our methodology addresses the lack of standardization in the literature that renders the comparison of approaches in different works meaningless, due to differences in metrics, environments, and even experimental design and methodology.

Experimental Design reinforcement-learning +1

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