85 citations · 93 across the 4 of their papers we have counts for
4 papers
A nonlinear hidden layer enables actor-critic agents to learn multiple paired association navigation
M Ganesh Kumar, Cheston Tan, Camilo Libedinsky +2
Navigation to multiple cued reward locations has been increasingly used to study rodent learning. Though deep reinforcement learning agents have been shown to be able to learn the…
One-shot learning of paired association navigation with biologically plausible schemas
M Ganesh Kumar, Cheston Tan, Camilo Libedinsky +2
After learning a multiple paired-association (MPA) navigation task, rodents can rapidly learn new cue-location associations after a single exposure, a phenomenon proposed to be fac…
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng +3
We present an improved method for symbolic regression that seeks to fit data to formulas that are Pareto-optimal, in the sense of having the best accuracy for a given complexity. I…
Approximating Boolean Functions with Disjunctive Normal Form
Yunhao Yang, Andrew Tan
The theorem states that: Every Boolean function can be by a Disjunctive Normal Form (DNF) of size . This paper will demonstrate this theorem in…