Eventi
29
Settembre
2022
29.
09.
2022
06
Ottobre
2022
06.
10.
2022
13
Ottobre
2022
13.
10.
2022
20
Ottobre
2022
20.
10.
2022
27
Ottobre
2022
27.
10.
2022
03
Novembre
2022
03.
11.
2022
10
Novembre
2022
10.
11.
2022

[email protected]: Dr Mattiheu Geist - Kalman Temporal Differences

Istituto Dalle Molle di studi sull’intelligenza artificiale

Data d'inizio: 22 Dicembre 2009

Data di fine: 23 Dicembre 2009

Dear Colleagues,

on Tuesday, 22nd of December, Dr Matthieu Geist will give us a talk titled: 
Kalman Temporal Differences
The place is: Sala Primavera, Galleria 2, 6928 Manno 

Abstract: 

Generalization is an important problem in reinforcement learning (RL), and value function approximation (VFA) is a way to handle it. A value function approximator should exhibit some features: being sample efficient (data can be expansive, especially in an industrial context), handling nonlinearities (nonlinear parameterization such as multilayer perceptron, Bellman optimality equation), handling nonstationarities (nonstationary system, but above all generalized policy iteration induces nonstationarities) and providing an uncertainty information about estimates (which should provide useful for the dilemma between exploration and exploitation). After a quick survey on VFA, it will be shown that casting value function approximation as a filtering problem allows introducing a framework which handles all these problems at the same time.