2019 42nd International Conference on Telecommunications and Signal Processing (TSP) 2019
DOI: 10.1109/tsp.2019.8768860
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Supervised Learning in Multi-Agent Environments Using Inverse Point of View

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Cited by 2 publications
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“…Reinforcement learning (RL) is also applied for the tank battling scenario of the RoboCode platform. In a recent study, the performance comparison between the GA and RL algorithm is done using different scenarios defined for the RoboCode environment [25]. An improved Q-learning technique in Semi-Markov decision processes is validated by using the RoboCode environment in [26].…”
Section: Battlingmentioning
confidence: 99%
“…Reinforcement learning (RL) is also applied for the tank battling scenario of the RoboCode platform. In a recent study, the performance comparison between the GA and RL algorithm is done using different scenarios defined for the RoboCode environment [25]. An improved Q-learning technique in Semi-Markov decision processes is validated by using the RoboCode environment in [26].…”
Section: Battlingmentioning
confidence: 99%