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SPEAKERS/AARON HUNTER
Aaron Hunter

Aaron Hunter

British Columbia Institute of Technology

Aaron's lectures

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Aaron Hunter · AGI-20

Learning to Model Another Agent's Beliefs: A Preliminary Approach

It is often useful for one agent to predict what another agent will believe after receiving new information. In fact, in order to appear intelligent in situations involving multiple interacting agents, we fundamentally need to be able to predict how changes in the world will affect the beliefs of others. This process involves two distinct processes. First, we need to devise a model that captures the way that beliefs change in response to new information. Second, we need to observe the behaviour of individual agents to determine their specific beliefs. In the AI literature, these problems have been addressed by distinct communities. In this paper, we bring these two communities together by demonstrating how an agent can learn a model of belief change from observed behaviour. We argue that this process is essential for natural interaction in an AGI setting, but it has not been addressed to date in a unified manner.

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Multiple speakers · AGI-20

AGI-20 Main Conference - Livestream Day 1

Coming soon

Multiple speakers · AGI-20

Panel Session 3: Learning, Reasoning, and Resource Allocation

Panel discussion with authors of papers about 'Learning, Reasoning, and Resource Allocation' at AGI-20 conference. Held live on Underline, 06/24/2020