Artificial Intelligence

1701 Submissions

[4] viXra:1701.0574 [pdf] submitted on 2017-01-22 21:33:04

The Relationship Between Agents and Link-Level Acknowledgements Using Mugwump

Authors: Thomas Lambert
Comments: 8 Pages.

In recent years, much research has been devoted to the improvement of architecture; unfortunately, few have explored the emulation of the World Wide Web. In fact, few biologists would disagree with the deployment of evolutionary programming. While this discussion is never a confirmed intent, it is derived from known results. Mugwump, our new framework for hash tables [28], is the solution to all of these challenges.
Category: Artificial Intelligence

[3] viXra:1701.0559 [pdf] submitted on 2017-01-21 11:05:33

AI Systems See the World as Humans

Authors: George Rajna
Comments: 38 Pages.

A Northwestern University team developed a new computational model that performs at human levels on a standard intelligence test. This work is an important step toward making artificial intelligence systems that see and understand the world as humans do. [25] Neuroscience and artificial intelligence experts from Rice University and Baylor College of Medicine have taken inspiration from the human brain in creating a new "deep learning" method that enables computers to learn about the visual world largely on their own, much as human babies do. [24]
Category: Artificial Intelligence

[2] viXra:1701.0530 [pdf] submitted on 2017-01-17 20:03:50

Intelligence of Crowd.

Authors: Michail Zak
Comments: 17 Pages.

A new class of dynamical systems with a preset type of interference of probabilities is introduced. It is obtained from the extension of the Madelung equation by replacing the quantum potential with a specially selected feedback from the Liouville equation. It has been proved that these systems are different from both Newtonian and quantum systems, but they can be useful for modeling spontaneous collective novelty phenomena when emerging outputs are qualitatively different from the weighted sum of individual inputs. Formation of language and fast decision-making process as potential applications of the probability interference is discussed.
Category: Artificial Intelligence

[1] viXra:1701.0516 [pdf] submitted on 2017-01-16 14:14:27

Optimal Control Via Self-Generated Stochasticity.

Authors: Michail Zak
Comments: 19 Pages.

Stochastic approach to maximization of a functional constrained by governing equation of a controlled system is introduced and discussed. The idea of the proposed algorithm is the following: represent the functional to be maximized as a limit of a probability density governed by the appropriately selected Liouville equation. Then the corresponding ODE become stochastic, and that sample of the solution which has the largest value will have the highest probability to appear in ODE simulation. Application to optimal control is discussed. Two limitations of optimal control theory - local maxima and possible instability of the optimal solutions - are removed. Special attention is paid to robot motion planning.
Category: Artificial Intelligence