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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning

Published in AAAI-26 oral, 2026

Value decomposition is a central approach in multi-agent reinforcement learning (MARL), enabling centralized training with decentralized execution by factorizing the global value function into local values.

Recommended citation: Tianmeng Hu, Yongzheng Cui, Rui Tang, Biao Luo, Ke Li. (2026). "Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning." AAAI2026.
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Autonomous Partner Selection for Cooperative Multi-Agent Reinforcement Learning

Published in AAAI-26 Poster, 2026

In cooperative Multi-Agent Reinforcement Learning (MARL), the subgroup-wise learning is employed to assign sub-tasks to agents towards the enhancement of team collaboration.

Recommended citation: Rui Tang, Biao Luo, Yongzheng Cui. " Autonomous Partner Selection for Cooperative Multi-Agent Reinforcement Learning" (2026).

HMU: Heuristic Memory Utilization for Multi-Agent Reinforcement Learning

Published in IEEE Transactions on Cognitive and Developmental Systems, 2026

In cooperative Multi-Agent Reinforcement Learning (MARL), agents attempt to complete the same task, such as defeating enemies and scoring goals. Due to the trial-and-error mechanism, MARL algorithms usually require a large amount of interactions with the environment to achieve convergence. .

Recommended citation: R. Tang et al., "HMU: Heuristic Memory Utilization for Multi-Agent Reinforcement Learning," in IEEE Transactions on Cognitive and Developmental Systems, doi: 10.1109/TCDS.2026.3685230.
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.