The GOMA algorithm casts human-robot communication as a planning problem by selecting utterances that maximizally improves the efficiency of the joint plan in a partially observable environment.

• Reward of robot sharing information X to human:
  $R$(request X) = KL($\mathbb{E}$[human plan | human mind + X] || $\mathbb{E}$[human plan | human mind ]) - $C$

• Reward of robot requesting information X from human:
  $R$(request X) = KL($\mathbb{E}$[robot plan | robot mind + X] || $\mathbb{E}$[robot plan | robot mind ]) - $C$

where C is the communication cost.

You can find a demonstration video on the website: lanceying.com/GOMA

The current implementation is tested in the virtual home domain. For installing virtual home, please clone this repo: https://github.com/xavierpuigf/virtualhome

To run the experiment use the following code:

python3 test_template_agent_structured.py --num-belief-particles 10 --num-proc 10 --model goma