Results 31 to 40 of about 1,196,266 (277)
LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward [PDF]
Neural Information Processing Systems, 2022 Episodic count has been widely used to design a simple yet effective intrinsic motivation for reinforcement learning with a sparse reward. However, the use of episodic count in a high-dimensional state space as well as over a long episode time requires a
DaeJin Jo +6 more
semanticscholar +1 more source
Counterfactual-Based Action Evaluation Algorithm in Multi-Agent Reinforcement Learning
Applied Sciences, 2022 Multi-agent reinforcement learning (MARL) algorithms have made great achievements in various scenarios, but there are still many problems in solving sequential social dilemmas (SSDs).
Yuyu Yuan +3 more
doaj +1 more source
Confirmation of interpersonal expectations is intrinsically rewarding [PDF]
Social Cognitive and Affective Neuroscience, 2020 Abstract People want to interact successfully with other individuals, and they invest significant efforts in attempting to do so. Decades of research have demonstrated that to simplify the dauntingly complex task of interpersonal communication, perceivers predict the responses of individuals in their environment using stereotypes and ...
Niv Reggev +2 more
openaire +3 more sources
Adherence Improves Cooperation in Sequential Social Dilemmas
Applied Sciences, 2022 Social dilemmas have guided research on mutual cooperation for decades, especially the two-person social dilemma. Most famously, Tit-for-Tat performs very well in tournaments of the Prisoner’s Dilemma. Nevertheless, they treat the options to cooperate or
Yuyu Yuan +3 more
doaj +1 more source
Skill-Based Reinforcement Learning with Intrinsic Reward Matching [PDF]
arXiv.org, 2022 While unsupervised skill discovery has shown promise in autonomously acquiring behavioral primitives, there is still a large methodological disconnect between task-agnostic skill pretraining and downstream, task-aware finetuning.
Ademi Adeniji, Amber Xie, P. Abbeel
semanticscholar +1 more source
Image Augmentation-Based Momentum Memory Intrinsic Reward for Sparse Reward Visual Scenes [PDF]
IEEE Transactions on Games, 2022 Many real-life tasks can be abstracted as sparse reward visual scenes, which can make it difficult for an agent to accomplish tasks accepting only images and sparse reward.
Zheng Fang, Biao Zhao, Guizhong Liu
semanticscholar +1 more source
Hierarchical Multi-Agent Reinforcement Learning with Intrinsic Reward Rectification
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023 Hierarchical reinforcement learning (HRL) is a promising approach to solving long-term decision problems and complex tasks, as high-level policy can guide the training procedure of low-level policy with macro actions and intrinsic rewards.
Zhihao Liu, Zhiwei Xu, Guoliang Fan
semanticscholar +1 more source
Scientific Reports, 2021 Behaviors driven by intrinsic motivation are critical for development and optimization of physical and brain functions, but their underlying mechanisms are not well studied due to the complexity and autonomy of the behavior.
Yunbok Kim +4 more
doaj +1 more source
Do Intrinsic Rewards Matter on Motivation?
SEISENSE Journal of Management, 2021 Purpose- This study investigates the impact of intrinsic rewards (Recognition, Training and Development, Work Environment, Participation in Decision Making, and Workplace Flexibility) on primary school teachers’ motivation at the workplace.
Nishath Anjum +3 more
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AIBPO: Combine the Intrinsic Reward and Auxiliary Task for 3D Strategy Game
Complexity, 2021 In recent years, deep reinforcement learning (DRL) achieves great success in many fields, especially in the field of games, such as AlphaGo, AlphaZero, and AlphaStar.
Huale Li +7 more
doaj +1 more source