Title
Learning to Prognostically Forage in a Neural Network Model of the Interactions between Neuromodulators and Prefrontal Cortex.
Abstract
Neuromodulatory systems and prefrontal cortex are involved in a number of decision-making contexts. In this work, we adapt a recent neural network model that simulates interactions between neuromodulatory and prefrontal areas to the problem of prognostic foraging—that is choosing information to update or form a hypothesis. In the context of a simulated geospatial intelligence task, the model assesses a number of decision variables and strategies to choose actions that maximize information utility to more accurately predict the actions of an adversary. The model is also capable of modeling biases in decision making such as deviations from the optimal solution of maximizing information gain. Comparisons to other approaches and problem domains in information foraging are also discussed.
Year
DOI
Venue
2014
10.1016/j.procs.2014.11.081
Procedia Computer Science
Keywords
Field
DocType
neuromodulators,prefrontal cortex,prognostic foraging
Information foraging,Decision variables,Geospatial intelligence,Computer science,Prefrontal cortex,Information gain,Information utility,Artificial intelligence,Adversary,Artificial neural network,Machine learning
Conference
Volume
ISSN
Citations 
41
1877-0509
1
PageRank 
References 
Authors
0.37
4
4
Name
Order
Citations
PageRank
Suhas E. Chelian142.21
Matthias D. Ziegler210.37
Peter Pirolli33661538.83
Rajan Bhattacharyya4215.60