Abstract
In this paper we propose an airline marketplace, modeled as a multi-agent system with an automated negotiation mechanism, where airlines can announce availability of resources (aircraft or aircraft and crew) for lease and other airlines can go there to contract resources to fill gaps in the operation, typically due to disruptions and/or an unexpected increase on the operation. The proposed negotiation occurs in several rounds, where qualitative comments made by the buyer agent on proposals sent by the sellers enables these to learn how to calculate new proposals, using a case-based reasoning methodology. © 2018, Springer International Publishing AG, part of Springer Nature.

Abstract

Abstract
With the rise in wearable technology and "Bhealth culture", we are seeing an increasing interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals' quality of life. On the one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health. In this paper, we evaluate the current state of the art in physiological therapy (biofeedback) along with the existing medical grade and consumer grade hardware for physiological research. We provide a quick primer on the most commonly monitored physiologic metrics, as well as a brief discussion on the current state of the art in biofeedback-assisted medical applications. We then go on to present a comparative analysis between medical and consumer grade biofeedback devices and discuss the hardware specifications and potential practical applications of each consumer grade device in terms of functionality and adaptability for controlled (laboratory) and uncontrolled (field) studies. We end this article with some empirical observations based on our study so that readers might use take them into consideration when arranging a laboratory or real-world experience, thus avoiding costly time delays and material expenditures.

Abstract
Serious games is a field of research that has evolved substantially with valuable contributions to many application domains and areas. Patients often consider traditional rehabilitation approaches to be repetitive and boring, making it difficult for them to maintain their ongoing interest and to assure the completion of the treatment program. This chapter reviews serious games and the natural and multimodal user interfaces for the health rehabilitation domain. Specifically, it details a framework for the development of serious games that integrates a rich set of features that can be used to improve the designed games with direct benefits to the rehabilitation process. Highlighted features include natural and multimodal interaction, social skills (collaboration and competitiveness), and progress monitoring. Due to the rich set of features supported by the framework, the games' rehabilitation efficacy can be enhanced primarily from an increase in the patient's motivation when exercising the rehabilitation tasks. A preliminary test of the framework with elderly users is described. © 2018, IGI Global.

Abstract

Abstract
Set plays are predefined collaborative coordinate actions that players from any sport can use to gain advantage over its adversaries. Recently, a complete framework for creation and execution of this kind of coordinate behavior by teams composed of multiple independent agents was launched as free software (the Set play Framework). In this paper, an approach based on Reinforcement Learning(RL) is proposed, that allows the use of experience to devise the better course of action in set plays with multiple choices. Simulations results show that the proposed approach allows a team of simulated agents to improve its performance against a known adversary team, achieving better results than previously proposed approaches using RL.