27,657 research outputs found
Hikester - the event management application
Today social networks and services are one of the most important part of our
everyday life. Most of the daily activities, such as communicating with
friends, reading news or dating is usually done using social networks. However,
there are activities for which social networks do not yet provide adequate
support. This paper focuses on event management and introduces "Hikester". The
main objective of this service is to provide users with the possibility to
create any event they desire and to invite other users. "Hikester" supports the
creation and management of events like attendance of football matches, quest
rooms, shared train rides or visit of museums in foreign countries. Here we
discuss the project architecture as well as the detailed implementation of the
system components: the recommender system, the spam recognition service and the
parameters optimizer
Role Playing Learning for Socially Concomitant Mobile Robot Navigation
In this paper, we present the Role Playing Learning (RPL) scheme for a mobile
robot to navigate socially with its human companion in populated environments.
Neural networks (NN) are constructed to parameterize a stochastic policy that
directly maps sensory data collected by the robot to its velocity outputs,
while respecting a set of social norms. An efficient simulative learning
environment is built with maps and pedestrians trajectories collected from a
number of real-world crowd data sets. In each learning iteration, a robot
equipped with the NN policy is created virtually in the learning environment to
play itself as a companied pedestrian and navigate towards a goal in a socially
concomitant manner. Thus, we call this process Role Playing Learning, which is
formulated under a reinforcement learning (RL) framework. The NN policy is
optimized end-to-end using Trust Region Policy Optimization (TRPO), with
consideration of the imperfectness of robot's sensor measurements. Simulative
and experimental results are provided to demonstrate the efficacy and
superiority of our method
- …