Transfer Learning (TL) has been shown to reduce learning time in single-agent, single-objective applications. It is the process of sharing knowledge between two ...
Jan 31, 2022 · In this paper, we propose Parallel Transfer Learning (PTL), an algorithm that accelerates learning in multi-objective, multi-agent systems. It ...
Abstract—Large-scale, multi-agent systems are too complex for optimal control strategies to be known at design time and as a result good strategies must be ...
A transfer learning approach is presented to address the challenge of training video game agents with limited data. The approach decomposes games into objects, ...
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Bibliographic details on Accelerating Learning in multi-objective systems through Transfer Learning.
[PDF] Accelerating Multiagent Reinforcement Learning through ...
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This research intends to acceler- ate learning in multiagent sequential decision-making tasks by reusing previous knowledge, both from past solutions and.
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Co-authors ; Accelerating Learning in Multi-Objective Systems through Transfer Learning. A Taylor, I Dusparic, E Galván-López, S Clarke, V Cahill. Special ...
Accelerating Multi-agent Reinforcement Learning with Dynamic Co-learning · Accelerating Learning in multi-objective systems through Transfer Learning.
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A hierarchical clustering-based manifold transfer learning (CMTL) method is developed for dynamic multi-objective optimization problems.
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