Therese Quieta
Papers
1
Total Citations
6
H-Index
1
About
Therese Quieta is a researcher at the intersection of artificial intelligence and cognitive science, with a primary focus on developing AI systems that emulate human-like performance. Her most cited work, "On Human-Like Performance Artificial Intelligence – A Demonstration Using an Atari Game" (2019), has garnered 6 citations and serves as a foundational demonstration of how AI can be trained to replicate human decision-making patterns in complex, real-time environments. By using the classic Atari game as a testbed, Quieta’s research bridges the gap between reinforcement learning and human behavioral modeling, offering insights into how machines can learn not just to win, but to think and act more naturally. This contribution is particularly notable for its potential applications in human-computer interaction, autonomous systems, and educational AI. Though early in her career, Quieta’s work signals a promising trajectory toward more intuitive and adaptable artificial intelligence, challenging conventional benchmarks of machine intelligence. Her research invites further exploration into how AI can mirror human cognition, making her a rising voice in the quest for truly human-centered AI.
Research Focus
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Top Papers
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