Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Son, Kyunghwan"'
Recently, graph-based planning algorithms have gained much attention to solve goal-conditioned reinforcement learning (RL) tasks: they provide a sequence of subgoals to reach the target-goal, and the agents learn to execute subgoal-conditioned polici
Externí odkaz:
http://arxiv.org/abs/2303.11166
Intrinsic rewards have been increasingly used to mitigate the sparse reward problem in single-agent reinforcement learning. These intrinsic rewards encourage the agent to look for novel experiences, guiding the agent to explore the environment suffic
Externí odkaz:
http://arxiv.org/abs/2210.16468
In this paper, we study a problem of detecting the source of diffused information by querying individuals, given a sample snapshot of the information diffusion graph, where two queries are asked: {\em (i)} whether the respondent is the source or not,
Externí odkaz:
http://arxiv.org/abs/2009.00795
QTRAN is a multi-agent reinforcement learning (MARL) algorithm capable of learning the largest class of joint-action value functions up to date. However, despite its strong theoretical guarantee, it has shown poor empirical performance in complex env
Externí odkaz:
http://arxiv.org/abs/2006.12010
Autor:
Song, Hyungseok, Jang, Hyeryung, Tran, Hai H., Yoon, Se-eun, Son, Kyunghwan, Yun, Donggyu, Chung, Hyoju, Yi, Yung
Publikováno v:
Proceedings of the Twenty-Eighth International Joint Conference Artificial Intelligence, {IJCAI-19} (2019), 3467--3474
We consider the Markov Decision Process (MDP) of selecting a subset of items at each step, termed the Select-MDP (S-MDP). The large state and action spaces of S-MDPs make them intractable to solve with typical reinforcement learning (RL) algorithms e
Externí odkaz:
http://arxiv.org/abs/1909.03638
We explore value-based solutions for multi-agent reinforcement learning (MARL) tasks in the centralized training with decentralized execution (CTDE) regime popularized recently. However, VDN and QMIX are representative examples that use the idea of f
Externí odkaz:
http://arxiv.org/abs/1905.05408
Autor:
Kim, Daewoo, Moon, Sangwoo, Hostallero, David, Kang, Wan Ju, Lee, Taeyoung, Son, Kyunghwan, Yi, Yung
Many real-world reinforcement learning tasks require multiple agents to make sequential decisions under the agents' interaction, where well-coordinated actions among the agents are crucial to achieve the target goal better at these tasks. One way to
Externí odkaz:
http://arxiv.org/abs/1902.01554
Social networks are the major routes for most individuals to exchange their opinions about new products, social trends and political issues via their interactions. It is often of significant importance to figure out who initially diffuses the informa
Externí odkaz:
http://arxiv.org/abs/1711.05496