Recent Publications

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In a single-agent setting, reinforcement learning (RL) tasks can be cast into an inference problem by introducing a binary random …

We propose a new reasoning protocol called generalized recursive reasoning (GR2), and embed it into the multi-agent reinforcement …

In this paper, we introduce a probabilistic recursive reasoning (PR2) framework for multi-agent reinforcement learning. Our hypothesis …

We conduct an empirical study on discovering the ordered collective dynamics obtained by a population of intelligence agents, driven by …

In typical reinforcement learning (RL), the environment is assumed given and the goal of the learning is to identify an optimal policy …



A Muti-agent Learning Framework.

Recent & Upcoming Talks

Most successful researches on reinforcement learning have been in single agent domain. However, many complex reinforcement learning …


Teaching Assistant @ University College London:

  • COMP1024: Multi-Agent Artificial Intelligence, 2019.
  • COMPGI15/M052: Information Retrieval and Data Mining, 2017-19.
  • COMPGW02/M041: Web Economics, Teaching Assistant, 2017-18.


  • University College London, Dept. of Computer Science, Gower Street, London WC1E 6BT, United Kingdom