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Full-Text Articles in Artificial Intelligence and Robotics

Large-Scale Discovery Of Visual Features For Object Recognition, Drew Linsley, Sven Eberhardt, Dan Shiebler, Thomas Serre May 2017

Large-Scale Discovery Of Visual Features For Object Recognition, Drew Linsley, Sven Eberhardt, Dan Shiebler, Thomas Serre

MODVIS Workshop

A central goal in vision science is to identify features that are important for object and scene recognition. Reverse correlation methods have been used to uncover features important for recognizing faces and other stimuli with low intra-class variability. However, these methods are less successful when applied to natural scenes with variability in their appearance.

To rectify this, we developed Clicktionary, a web-based game for identifying features for recognizing real-world objects. Pairs of participants play together in different roles to identify objects: A “teacher” reveals image regions diagnostic of the object’s category while a “student” tries to recognize the object. Aggregating …


Curiosity: Emergent Behavior Through Interacting Multi-Level Predictions, Douglas S. Blank, Lisa Meeden, James Marshall May 2017

Curiosity: Emergent Behavior Through Interacting Multi-Level Predictions, Douglas S. Blank, Lisa Meeden, James Marshall

Computer Science Faculty Research and Scholarship

Over the past 15 years our research group has been exploring models of developmental robotics and curiosity. Our research is based on the premise that intelligent behavior arises through emergent interactions between opposing forces in an open-ended, task-independent environment. In an initial experiment we constructed a recurrent neural network model where self-motivation was "an emergent property generated by the competing pressures that arise in attempting to balance predictability and novelty". The system first focused on its error, then learned to successfully predict its error, and finally became habituated to what caused the error. This process of focusing, learning, and habituating …


Investigating Trust And Trust Recovery In Human-Robot Interactions, Abigail L. Thomson May 2017

Investigating Trust And Trust Recovery In Human-Robot Interactions, Abigail L. Thomson

Celebration of Learning

As artificial intelligence and robotics continue to advance and be used in increasingly different functions and situations, it is important to look at how these new technologies will be used. An important factor in how a new resource will be used is how much it is trusted. This experiment was conducted to examine people’s trust in a robotic assistant when completing a task, how mistakes affect this trust, and if the levels of trust exhibited with a robot assistant were significantly different than if the assistant were human. The task was to watch a computer simulation of the three-cup monte …


A Day In The Life Of A Sim: Making Meaning Of Video Game Avatars And Behaviors, Jessica Stark Jan 2017

A Day In The Life Of A Sim: Making Meaning Of Video Game Avatars And Behaviors, Jessica Stark

Antioch University Dissertations & Theses

With video game usage--and criticism on its activity--on the rise, it may be helpful for the psychological community to understand what it actually means to play video games, and what the lived experience entails. This qualitative, phenomenological study specifically explores user behaviors and decisions in the simulated life video game, The Sims. Ten participants completed one- to two-hour long semi-structured interviews, and the data was transcribed, organized into 1,988 codes, which were clustered into 30 categories, and from which six themes ultimately emerged. These resulting themes are: self-representation; past, present, and future; purpose for play; self-reflection; co-creation; and familiarity. The …