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Scale invariant robot behavior with fractals

arXiv.org Artificial Intelligence

Robots deployed at orders of magnitude different size scales, and that retain the same desired behavior at any of those scales, would greatly expand the environments in which the robots could operate. However it is currently not known whether such robots exist, and, if they do, how to design them. Since self similar structures in nature often exhibit self similar behavior at different scales, we hypothesize that there may exist robot designs that have the same property. Here we demonstrate that this is indeed the case for some, but not all, modular soft robots: there are robot designs that exhibit a desired behavior at a small size scale, and if copies of that robot are attached together to realize the same design at higher scales, those larger robots exhibit similar behavior. We show how to find such designs in simulation using an evolutionary algorithm. Further, when fractal attachment is not assumed and attachment geometries must thus be evolved along with the design of the base robot unit, scale invariant behavior is not achieved, demonstrating that structural self similarity, when combined with appropriate designs, is a useful path to realizing scale invariant robot behavior. We validate our findings by demonstrating successful transferal of self similar structure and behavior to pneumatically-controlled soft robots. Finally, we show that biobots can spontaneously exhibit self similar attachment geometries, thereby suggesting that self similar behavior via self similar structure may be realizable across a wide range of robot platforms in future.


Research: How One Bad Employee Can Corrupt a Whole Team

#artificialintelligence

One bad apple, the saying goes, can ruin the bunch. Our research on the contagiousness of employee fraud tells us that even your most honest employees become more likely to commit misconduct if they work alongside a dishonest individual. And while it would be nice to think that the honest employees would prompt the dishonest employees to better choices, that's rarely the case. Among co-workers, it appears easier to learn bad behavior than good. For managers, it is important to realize that the costs of a problematic employee go beyond the direct effects of that employee's actions -- bad behaviors of one employee spill over into the behaviors of other employees through peer effects.


Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior

AAAI Conferences

In recent years online social networks have suffered an increase in sexism, racism, and other types of aggressive and cyberbullying behavior, often manifesting itself through offensive, abusive, or hateful language. Past scientific work focused on studying these forms of abusive activity in popular online social networks, such as Facebook and Twitter. Building on such work, we present an eight month study of the various forms of abusive behavior on Twitter, in a holistic fashion. Departing from past work, we examine a wide variety of labeling schemes, which cover different forms of abusive behavior. We propose an incremental and iterative methodology that leverages the power of crowdsourcing to annotate a large collection of tweets with a set of abuse-related labels. By applying our methodology and performing statistical analysis for label merging or elimination, we identify a reduced but robust set of labels to characterize abuse-related tweets. Finally, we offer a characterization of our annotated dataset of 80 thousand tweets, which we make publicly available for further scientific exploration.


Using Reactive and Adaptive Behaviors to Play Soccer

AI Magazine

This work deals with designing simple behaviors to allow quadruped robots to play soccer. In addition to vision problems such as changing lighting conditions and color confusion, legged robots must cope with "bouncing images" because of successive legs hitting the ground. Because it is not always possible to simulate the problems encountered in real situations, the behavior strategy should anticipate them. Experiments were carried out at the 1999 RoboCup in Stockholm using the Sony quadruped robots (Fujita 2000).


Cognitive bias cheat sheet

#artificialintelligence

I've spent many years referencing Wikipedia's list of cognitive biases whenever I have a hunch that a certain type of thinking is an official bias but I can't recall the name or details. It's been an invaluable reference for helping me identify the hidden flaws in my own thinking. Nothing else I've come across seems to be both as comprehensive and as succinct. However, honestly, the Wikipedia page is a bit of a tangled mess. Despite trying to absorb the information of this page many times over the years, very little of it seems to stick.