Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
Abstract This paper provides details on the development of a tool to aid in 3D coral reef mapping designed to be operated by a single diver and later integrated into an autonomous ...
Andrew Hogue, Andrew German, James E. Zacher, Mich...
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
In this paper, a three-component architecture of a learning environment for Go is sketched, which can be applied to any two-player, deterministic, full information, partizan, comb...
Abstract— Many robotic control tasks involve complex dynamics that are hard to model. Hand-specifying trajectories that satisfy a system’s dynamics can be very time-consuming a...
Jie Tang, Arjun Singh, Nimbus Goehausen, Pieter Ab...