Dear all,
We will have our next LIRa session on Thursday, November 19th. Our speaker is Andrés Occhipinti Liberman. You can find the details of the talk below. We will use our recurring zoom link: https://uva-live.zoom.us/j/92907704256?pwd=anY3WkFmQVhLZGhjT2JXMlhjQVl1dz09 (Meeting ID: 929 0770 4256, Passcode: 036024).
Date and Time: Thursday, November 19th 2020, 16:30-18:00, Amsterdam time.
Venue: online.
Title: Learning to Act and Observe in Partially Observable Domains
Abstract.
We consider a learning agent in a partially observable domain (or environment), with which the agent has never interacted before. The agent wishes to learn a representation of the domain dynamics: how the agent's actions affect the state of the domain and what becomes observable as a result of such actions. To produce such knowledge, the learner has access to experience gathered by taking actions in the domain and observing their results.
We present algorithms for learning "as much as possible" (in a well-defined sense) both about what is directly observable and about what actions do in the domain, given the learner's observational constraints. We differentiate the level of domain knowledge attained by each algorithm, and characterize the type of observations required to reach it. The algorithms use dynamic epistemic logic (DEL) to represent the learned domain information symbolically. Our work continues that of Bolander and Gierasimczuk (2015), which developed DEL-based learning algorithms based to learn domain information in fully observable domains.
This is joint work with Thomas Bolander and Nina Gierasimczuk.
Hope to see you there!
The LIRa team