Gilson A. Giraldi
Papers
1
Total Citations
15
H-Index
1
About
Gilson A. Giraldi is a researcher whose work sits at the intersection of computer vision, machine learning, and cognitive robotics. His key research areas include attentional control, reinforcement learning, and multi-modal perception. In his notable 2003 paper, "Learning policies for attentional control," Giraldi tackles the challenge of enabling agents to actively select what to perceive in complex environments. He proposes two distinct policies for attentional control driven by multi-modal sensory feedback: a straightforward heuristic strategy and a more sophisticated approach using Q-learning to derive an optimal policy based on the agent's perceptual state. This work, which has garnered 15 citations, demonstrates an early and insightful application of reinforcement learning to the problem of active perception, bridging the gap between low-level sensory processing and high-level cognitive control. Giraldi's contributions are particularly relevant for researchers interested in developing autonomous systems that can efficiently allocate computational resources by learning where and how to focus attention.
Research Focus
Key Achievements
Top Papers
- 1Learning policies for attentional control15 citations · 2003