Active Sensing as Bayes-Optimal Sequential Decision Making

08/09/2014
by   Sheeraz Ahmad, et al.
0

Sensory inference under conditions of uncertainty is a major problem in both machine learning and computational neuroscience. An important but poorly understood aspect of sensory processing is the role of active sensing. Here, we present a Bayes-optimal inference and control framework for active sensing, C-DAC (Context-Dependent Active Controller). Unlike previously proposed algorithms that optimize abstract statistical objectives such as information maximization (Infomax) [Butko & Movellan, 2010] or one-step look-ahead accuracy [Najemnik & Geisler, 2005], our active sensing model directly minimizes a combination of behavioral costs, such as temporal delay, response error, and effort. We simulate these algorithms on a simple visual search task to illustrate scenarios in which context-sensitivity is particularly beneficial and optimization with respect to generic statistical objectives particularly inadequate. Motivated by the geometric properties of the C-DAC policy, we present both parametric and non-parametric approximations, which retain context-sensitivity while significantly reducing computational complexity. These approximations enable us to investigate the more complex problem involving peripheral vision, and we notice that the difference between C-DAC and statistical policies becomes even more evident in this scenario.

READ FULL TEXT

Authors

page 6

01/27/2021

Statistical guided-waves-based SHM via stochastic non-parametric time series models

Damage detection in active-sensing, guided-waves-based Structural Health...
06/25/2020

Inverse Active Sensing: Modeling and Understanding Timely Decision-Making

Evidence-based decision-making entails collecting (costly) observations ...
12/04/2021

Active Sensing for Search and Tracking: A Review

Active Position Estimation (APE) is the task of localizing one or more t...
06/27/2012

Bayesian Optimal Active Search and Surveying

We consider two active binary-classification problems with atypical obje...
02/09/2014

Better Optimism By Bayes: Adaptive Planning with Rich Models

The computational costs of inference and planning have confined Bayesian...
11/20/2018

Geometry of Friston's active inference

We reconstruct Karl Friston's active inference and give a geometrical in...
08/06/2021

Anomaly Search with Multiple Plays under Delay and Switching Costs

The problem of searching for L anomalous processes among M processes is ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.