而对比 Multi-Game Decision Transformer 和其他模型在雅塔利游戏中的性能表现,可以看到,该模型的性能随大小稳定增长,而其他模型都在大小增长到一定水平之后性能达到饱和不增再加,且性能随模型大小的增长相对缓慢得多。 研究人员还评估了经过预训练的和未经预训练的 Multi-Game Decision Transformer 模型与其他模型在微调...
而对比 Multi-Game Decision Transformer 和其他模型在雅塔利游戏中的性能表现,可以看到,该模型的性能随大小稳定增长,而其他模型都在大小增长到一定水平之后性能达到饱和不增再加,且性能随模型大小的增长相对缓慢得多。 研究人员还评估了经过预训练的和未经预训练的 Multi-Game Decision Transformer 模型与其他模型在微调...
基础模型大致setting与Decision Transformer类似 但是优化了DT的输入,DT中是(Rg, s->a),而本文变为了给定(s0, s1, ..., si),要求先去预测Return-to-go的分布,然后从Return-to-go的分布中采样出对应action,同时估计即时reward(作为辅助任务),这样做的优点是通过估计Return-to-go的分布,降低了rtg不确定性对模...
During the training process, we propose multi-agent independent soft actor-critic to facilitate policy improvement and generate offline dataset, and propose multi-agent independent decision transformer for model training in the UPE game. Extensive simulations demonstrate the scalability and generalization ...
we facilitate the research by providing large-scale datasets and using them to examine the usage of the decision transformer in the context of MARL.We investigate the generalization of MARL offline pre-training in the following three aspects:1)between single agents and multiple agents,2)from ...
Attention over self-attention: Intention-aware re-ranking with dynamic transformer encoders for recommendation. arXiv preprint arXiv:2201.05333, 2022. Liu et al. [2019] Weiwen Liu, Jun Guo, Nasim Sonboli, Robin Burke, and Shengyu Zhang. Personalized fairness-aware re-ranking for microlending...
nlptext-classificationtaggingtransformerstext-generationtaggertext-processingmulti-label-classificationmulti-tasktransformer-models UpdatedMay 1, 2023 Python Roof Classification, Segmentation, and Damage Completion using 3D Point Clouds computer-visionpoint-clouddeeplearningmulti-taskroofpointcloudroofn3droof-classifi...
Short-range air combat maneuver decision of UAV swarm based on multi-agent Transformer introducing virtual objects Multi-agent transformerVirtual objectReinforcement learningWith the development of Unmanned Aerial Vehicle (UAV) swarm technology, there has been a growing ... F Jiang,M Xu,Y Li,... ...
研究人员提出了一种Multi-Game Decision Transformer通用结构,能够有效的执行多种任务和快速的学习决策新任务。 模型利用基于 transformer 的模型在 offline 情况下训练出在46个 atari 游戏中接近人类玩家水平的智能体。同时,该模型在视觉和语言任务中的某些方面,包括模型尺寸对表现的影响(文章使用 power-law 来说明)和...
决策型Mask Image Model(Decision-based MIM)是这篇论文中提出的一个核心概念,用于解决神经元分割任务中的一系列挑战。具体来说,决策型MIM有以下几个关键特点: 自动选择遮罩比例和策略:通过使用多智能体强化学习(MARL),该模型能够自动地搜索最适合的图像遮罩比例和遮罩策略,从而消除了手动调整这些参数的需要(第1页和...