Bella Veksler :: CogWorks Laboratories :: Rensselaer Polytechnic Institute / RPI

Bella Z. Veksler

Phone: 518.276.6067

~"They made the machines. That's what I'm trying to tell you. Meat made the machines."

~"That's ridiculous. How can meat make a machine? You're asking me to believe in sentient meat."

~"Yes, thinking meat! Conscious meat! Loving meat. Dreaming meat. The meat is the whole deal! Are you getting the picture?"

-Terry Bisson (THEY'RE MADE OUT OF MEAT)

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In sum, the Spivey Test demonstrates that computer-like reasoning is, for the most part, just as difficult for humans to display as human-like reasoning is for an AI to display.

-Michael Spivey (Turning the Tables on the Turing Test, the Spivey Test)

Bella was born in a small village in Ukraine and immigrated to the US in 1993. After completing high school in New Jersey, she went on to "gorges" Ithaca, NY to attend Cornell University. She was a double major and received her Bachelor of Arts degree in Computer Science and Psychology and concentration in Cognitive Science from Cornell. Deciding to stick with the Greek cities, she is now in Troy, NY as a third year doctoral student at the Department of Cognitive Science in RPI.

Publications

Zafrina, B., Veksler, V. D., Gamard, S., & Gray, W. D. (2006). Tetris as a Task Environment for Research in Dynamic Decision Making, Attention, Categorization, and Cognitive Modeling. In Sun, R., & Miyake, N. (Eds.). Proceedings of the 28th Annual Conference of the Cognitive Science Society (p. 2637). Hillsdale, NJ: Lawrence Erlbaum.

Veksler, B. Z., Gray, W. D., Schoelles, M. J. (2007). ProtoMatch: A Tool for Manipulating Eye, Mouse, and Keystroke Data. Proceedings of the 29th Annual Conference of the Cognitive Science Society. (download available)

Veksler, B. Z., Gray, W. D., Schoelles, M. J. (2007). From 1000ms to 650ms: Why Interleaving, Soft Constraints, and Milliseconds Matter. Proceedings of the 8th International Conference on Cognitive Modeling. (download available)

Veksler, B. Z., Gray, W. D. (2008). Counting Sheep is a Good Way to get to Sleep, but The Occasional Aardvark Will Wake You Up: How a Salient Event Improves Performance. Proceedings of the 30th Annual Meeting of the Cognitive Science Society.

Research Projects

Argus.
Argus is a radar simulation that containins approaching airships. Each airship varies across seven attributes, such as speed, altitude, distance from ownship, etc. The primary task is to classify the threat of each airship. Argus was developed to support research in measuring and modeling cognitive workload. Argus can be used in single-subject and team modes.

Argus Prime.
Argus Prime is a series of experiments using the Argus Simulated Task Environment that are focused on determining how humans operate within a dynamic environment. The series of studies include dual-task and interruption conditions while an operator classifies the threat-level of incoming aircraft (see Argus ).

Decision-Making Argus Prime.
Over the last two decades attempts to quantify decision-making have established that, under a wide range of conditions, people trade-off effectiveness for efficiency in the strategies they adopt. However, as interesting, significant, and influential as this research has been, its scope is limited by three factors; the coarseness of how effort was measured, the confounding of the costs of steps in the decision-making algorithm with the costs of steps in a given task environment, and the static nature of the decision tasks studied. Across a series of experiments, we embed decision-making tasks into dynamic task environments and vary the cost required for various steps. Across studies, small changes in the cost of interactive behavior leads to changes in the strategy adopted for decision-making as well as to differences in how a step in the same strategy is implemented. Work is proceeding to construct a family of ACT-R models, simBorgs, that perform aspects of the DMAP tasks in the same way as humans.

Tetris.
Apart from being a game that we all know and love, Tetris is also a relatively complex cognitive task that requires dynamic task processing, advanced perceptual capabilities, and involves both top-down and bottom-up strategies. Given the lack of cognitive models designed for such dynamic tasks, we explore the Tetris environment as a way to get at human perception, learning and memory, categorization, attention, and procedure/strategy selection.