2000 character limit reached
Enhancing Agent Communication and Learning through Action and Language (2308.10842v3)
Published 18 Aug 2023 in cs.AI and cs.LG
Abstract: We introduce a novel category of GC-agents capable of functioning as both teachers and learners. Leveraging action-based demonstrations and language-based instructions, these agents enhance communication efficiency. We investigate the incorporation of pedagogy and pragmatism, essential elements in human communication and goal achievement, enhancing the agents' teaching and learning capabilities. Furthermore, we explore the impact of combining communication modes (action and language) on learning outcomes, highlighting the benefits of a multi-modal approach.
- A survey of robot learning from demonstration. Robotics and autonomous systems, 57(5):469–483, 2009.
- Overcoming referential ambiguity in language-guided goal-conditioned reinforcement learning. arXiv preprint arXiv:2209.12758, 2022a.
- Pragmatically learning from pedagogical demonstrations in multi-goal environments. In Advances in Neural Information Processing Systems, 2022b.
- Autotelic agents with intrinsically motivated goal-conditioned reinforcement learning: a short survey. Journal of Artificial Intelligence Research, 74:1159–1199, 2022.
- Gweon, H. Inferential social learning: cognitive foundations of human social learning and teaching. Trends in Cognitive Sciences, 2021.
- Showing versus doing: Teaching by demonstration. In NeurIPS, 2016.
- Communication in action: Planning and interpreting communicative demonstrations, 2019.
- A rational account of pedagogical reasoning: Teaching by, and learning from, examples. Cognitive psychology, 71:55–89, 2014.
- Towards teachable autonomous agents. arXiv preprint arXiv:2105.11977, 2021.
- Show or tell? demonstration is more robust to changes in shared perception than explanation. arXiv preprint arXiv:2012.09035, 2020.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.