63,501 research outputs found
Collective behavior and evolutionary games - An introduction
This is an introduction to the special issue titled "Collective behavior and
evolutionary games" that is in the making at Chaos, Solitons & Fractals. The
term collective behavior covers many different phenomena in nature and society.
From bird flocks and fish swarms to social movements and herding effects, it is
the lack of a central planner that makes the spontaneous emergence of sometimes
beautifully ordered and seemingly meticulously designed behavior all the more
sensational and intriguing. The goal of the special issue is to attract
submissions that identify unifying principles that describe the essential
aspects of collective behavior, and which thus allow for a better
interpretation and foster the understanding of the complexity arising in such
systems. As the title of the special issue suggests, the later may come from
the realm of evolutionary games, but this is certainly not a necessity, neither
for this special issue, and certainly not in general. Interdisciplinary work on
all aspects of collective behavior, regardless of background and motivation,
and including synchronization and human cognition, is very welcome.Comment: 6 two-column pages, 1 figure; accepted for publication in Chaos,
Solitons & Fractals [the special issue is available at
http://www.sciencedirect.com/science/journal/09600779/56
Introducing Risk Shadowing For Decisive and Comfortable Behavior Planning
We consider the problem of group interactions in urban driving.
State-of-the-art behavior planners for self-driving cars mostly consider each
single agent-to-agent interaction separately in a cost function in order to
find an optimal behavior for the ego agent, such as not colliding with any of
the other agents. In this paper, we develop risk shadowing, a situation
understanding method that allows us to go beyond single interactions by
analyzing group interactions between three agents. Concretely, the presented
method can find out which first other agent does not need to be considered in
the behavior planner of an ego agent, because this first other agent cannot
reach the ego agent due to a second other agent obstructing its way. In
experiments, we show that using risk shadowing as an upstream filter module for
a behavior planner allows to plan more decisive and comfortable driving
strategies than state of the art, given that safety is ensured in these cases.
The usability of the approach is demonstrated for different intersection
scenarios and longitudinal driving.Comment: Accepted at IEEE ITSC 202
Recommended from our members
STRATEGIST : a program that models strategy-driven and content-driven inference behavior
In the course of understanding a text, different readers use different inference strategies to guide their choice of interpretations of the events in the text. This is in contrast to previous computer models of understanding, which all use the content-driven inference. The separate strategies are theorized to be composed of the same component inference processes, but of different rules for application of the processes. The use of different strategies occasionally results in different results of new experimental data and a working computer program, called STRATEGIST, that models both strategy-drive and content-driven inference behavior. The rules which make up two of these strategies are presented
Limited Visibility and Uncertainty Aware Motion Planning for Automated Driving
Adverse weather conditions and occlusions in urban environments result in
impaired perception. The uncertainties are handled in different modules of an
automated vehicle, ranging from sensor level over situation prediction until
motion planning. This paper focuses on motion planning given an uncertain
environment model with occlusions. We present a method to remain collision free
for the worst-case evolution of the given scene. We define criteria that
measure the available margins to a collision while considering visibility and
interactions, and consequently integrate conditions that apply these criteria
into an optimization-based motion planner. We show the generality of our method
by validating it in several distinct urban scenarios
Behavioural decisions & policy
We study the public policy implications of a model in which agents do not fully internalize all the conscequences of their actions. Such a model uni…es seemingly disconected models with behavioral agents. We evaluate the scope of
paternalistic and libertarian-parternalistic policies in the light of our model, and propose an alternative type of approach, called soft-libertarian, which guides
the decision makers in the internalization of all the conscequences of their actions.
Psychotherapy is one example of a soft-libertarian policy. Moreover, we show that in our behavioral framework, policies that increase the set of opportunities
or provide more information to the agent may not longer be individual welfare improving
Federated Robust Embedded Systems: Concepts and Challenges
The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements.
While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development.
During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs
MaestROB: A Robotics Framework for Integrated Orchestration of Low-Level Control and High-Level Reasoning
This paper describes a framework called MaestROB. It is designed to make the
robots perform complex tasks with high precision by simple high-level
instructions given by natural language or demonstration. To realize this, it
handles a hierarchical structure by using the knowledge stored in the forms of
ontology and rules for bridging among different levels of instructions.
Accordingly, the framework has multiple layers of processing components;
perception and actuation control at the low level, symbolic planner and Watson
APIs for cognitive capabilities and semantic understanding, and orchestration
of these components by a new open source robot middleware called Project Intu
at its core. We show how this framework can be used in a complex scenario where
multiple actors (human, a communication robot, and an industrial robot)
collaborate to perform a common industrial task. Human teaches an assembly task
to Pepper (a humanoid robot from SoftBank Robotics) using natural language
conversation and demonstration. Our framework helps Pepper perceive the human
demonstration and generate a sequence of actions for UR5 (collaborative robot
arm from Universal Robots), which ultimately performs the assembly (e.g.
insertion) task.Comment: IEEE International Conference on Robotics and Automation (ICRA) 2018.
Video: https://www.youtube.com/watch?v=19JsdZi0TW
Financial Coaching: A New Approach for Asset Building?
Through a literature review and interviews with nonprofit financial coaches, examines the concepts, training, and capacity building involved in financial coaching for low-income families, as well as critiques of existing models and their implications
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