Learning in peer-to-peer markets: evidence from Airbnb

Peer-to-peer markets are highly uncertain environments due to the constant presence of shocks. As a consequence, sellers have to constantly adjust to these shocks. Dynamic Pricing is hard, especially for non-professional sellers. We study it in an accommodation rental marketplace, Airbnb. With scraped data from its website, we: 1) describe pricing patterns consistent with learning; 2) estimate a demand model and use it to simulate a dynamic pricing model. We simulate it under three scenarios: a) with learning; b) without learning; c) with full information. We have found that information is an important feature concerning rental markets. Furthermore, we have found that learning is important for hosts to improve their profits.

Time-place learning in food-restricted Nile tilapia

Time-place learning based on food association was investigated in eight food-restricted Nile tilapias. Each fish was individually housed for 10 days in an experimental tank for adjustments to laboratory conditions, and fed daily in excess. Feeding was then interrupted for 17 days. Training was then started, based on a food-restricted regime in a tank divided into three interconnected compartments. Daily food was offered in one compartment (left or right side) of the tank in the morning and on the opposite side in the afternoon, for a continuous 30-day period. Frequency of choices on the right side was measured on days 10, 20 and 30 (during these test days, fish were not fed). Following this 30-day conditioning period, the Nile tilapias were able to switch sides at the correct period of the day to get food, suggesting that food restriction facilitates time-place learning discrimination. (C) 2007 Elsevier B.V. All rights reserved.

Testing time-place learning in the cichlid fish Nile tilapia

Time-place learning based on food association was investigated in the fish Nile tilapia. During a 30-day period, food was placed at one side of the aquarium (containing three compartments) in the morning and at the opposite side in the afternoon. Learning was inferred by the number of correct side choices of all fish in each day of test (15th, 30th). During the test day, fish were not fed. The Nile tilapia did not learn to switch sides at the correct day period in order to get food, suggesting thus that this species does not have time-place learning ability.

Time-place learning in individually reared angelfish, but not in pearl cichlid

Time-place learning based on food association was investigated in the cichlids angelfish (Pterophyllum scalare) and pearl cichlid (Geophagus brasiliensis) reared in isolation, therefore eliminating social influence on foraging. During a 30-day period, food was placed in one side of the aquarium (containing three compartments) in the morning and in the opposite side in the afternoon. Learning was inferred by the number of correct side choices of all fish in each day of test (15th and 30th). During the test day fish were not fed. The angelfish learned to switch sides at the correct day period in order to get food, suggesting this species has time-place learning ability when individually reared. on the other hand, the same was not observed for pearl cichlid. (c) 2006 Elsevier B.V. All rights reserved.

Relational learning in children with deafness and cochlear implants

This four-experiment series sought to evaluate the potential of children with neurosensory deafness and cochlear implants to exhibit auditory-visual and visual-visual stimulus equivalence relations within a matching-to-sample format. Twelve children who became deaf prior to acquiring language (prelingual) and four who became deaf afterwards (postlingual) were studied. All children learned auditory-visual conditional discriminations and nearly all showed emergent equivalence relations. Naming tests, conducted with a subset of the: children, showed no consistent relationship to the equivalence-test outcomes.. This study makes several contributions: to the literature on stimulus equivalence. First; it demonstrates that both pre- and postlingually deaf children-can: acquire auditory-visual equivalence-relations after cochlear implantation, thus demonstrating symbolic functioning. Second, it directs attention to a population that may be especially interesting for researchers seeking to analyze the relationship. between speaker and listener repertoires. Third, it demonstrates the feasibility of conducting experimental studies of stimulus control processes within the limitations of a hospital, which these children must visit routinely for the maintenance of their cochlear implants.

A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

Labour markets, worker protection and lifelong learning in a global economy: experiences and perspectives of Latin America and the Caribbean

Includes bibliography

Collaborative language learning in Teletandem: a resource for pre-service teacher education

This article presents some of the results of a qualitative research project about the influences of the pedagogic strategies used by a mediator (graduate student in applied linguistics) in the supervision process of a Teletandem partner (undergraduate student in languages) on her pedagogical practice. It was done within the project Teletandem Brazil: foreign language for all. Based on the reflective teaching paradigm and collaborative language learning, with special emphasis on tandem learning, we analyzed the contributions of the collaborative relationship established between the graduate student and the student-teacher in her first teaching experience. The results bring about implications for the field of language teacher education in a perspective of education within practice, evidencing the experience of collaborative learning in teletandem as an opportunity for reflective teacher education of pre-service teachers.

Awareness of Daylighting on Student Learning in an Educational Facility

This study examines how awareness of the interior architecture of a building, specifically daylighing, affects students academic performance. Extensive research has proven that the use of daylighting in a classroom can significantly enhance students’ academic success. The problem statement and purpose of this study is to determine if student awareness of daylighting in their learning environment affects academic performance compared to students with no knowledge of daylighting. Research and surveys in existing and newly constructed high schools were conducted to verify the results of this study. These design ideas and concepts could influence the architecture and design industry to advocate construction and building requirements that incorporate more sustainable design teaching techniques.

Word sense disambiguation via high order of learning in complex networks

Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.