May We Have Your Attention: Analysis of a Selective Attention Task

2006/06/29 by Eldan Goldenberg, Goldenberg, Eldan, Jacob R Garcowski +3
Neuroscience · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE) #Neuroscience, Education and Cognitive Function

paper · pdf · doi:10.48550/arxiv.cs/0606126

openalex publication_date 2006/06/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we present a deeper analysis than has previously been carried out of a selective attention problem, and the evolution of continuous-time recurrent neural networks to solve it. We show that the task has a rich structure, and agents must solve a variety of subproblems to perform well. We consider the relationship between the complexity of an agent and the ease with which it can evolve behavior that generalizes well across subproblems, and demonstrate a shaping protocol that improves generalization.

Citations

• The Dynamics of Active Categorical Perception in an Evolved Model Agent

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