73 citations · 113 across the 4 of their papers we have counts for
4 papers
Modular Adaptive Policy Selection for Multi-Task Imitation Learning through Task Division
Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim
Deep imitation learning requires many expert demonstrations, which can be hard to obtain, especially when many tasks are involved. However, different tasks often share similarities…
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning
Jianhong Wang, Yuan Zhang, Yunjie Gu +1
Value factorisation is a useful technique for multi-agent reinforcement learning (MARL) in global reward game, however its underlying mechanism is not yet fully understood. This pa…
Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System
Jianhong Wang, Yuan Zhang, Tae-Kyun Kim +1
Designing task-oriented dialogue systems is a challenging research topic, since it needs not only to generate utterances fulfilling user requests but also to guarantee the comprehe…
Shapley Q-value: A Local Reward Approach to Solve Global Reward Games
Jianhong Wang, Yuan Zhang, Tae-Kyun Kim +1
Cooperative game is a critical research area in the multi-agent reinforcement learning (MARL). Global reward game is a subclass of cooperative games, where all agents aim to maximi…