11,358 research outputs found
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
This paper describes an approach to the design of a population of cooperative
robots based on concepts borrowed from Systems Theory and Artificial
Intelligence. The research has been developed under the SocRob project, carried
out by the Intelligent Systems Laboratory at the Institute for Systems and
Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the
project stands both for "Society of Robots" and "Soccer Robots", the case study
where we are testing our population of robots. Designing soccer robots is a
very challenging problem, where the robots must act not only to shoot a ball
towards the goal, but also to detect and avoid static (walls, stopped robots)
and dynamic (moving robots) obstacles. Furthermore, they must cooperate to
defeat an opposing team. Our past and current research in soccer robotics
includes cooperative sensor fusion for world modeling, object recognition and
tracking, robot navigation, multi-robot distributed task planning and
coordination, including cooperative reinforcement learning in cooperative and
adversarial environments, and behavior-based architectures for real time task
execution of cooperating robot teams
Cram\'er-Rao bounds for synchronization of rotations
Synchronization of rotations is the problem of estimating a set of rotations
R_i in SO(n), i = 1, ..., N, based on noisy measurements of relative rotations
R_i R_j^T. This fundamental problem has found many recent applications, most
importantly in structural biology. We provide a framework to study
synchronization as estimation on Riemannian manifolds for arbitrary n under a
large family of noise models. The noise models we address encompass zero-mean
isotropic noise, and we develop tools for Gaussian-like as well as heavy-tail
types of noise in particular. As a main contribution, we derive the
Cram\'er-Rao bounds of synchronization, that is, lower-bounds on the variance
of unbiased estimators. We find that these bounds are structured by the
pseudoinverse of the measurement graph Laplacian, where edge weights are
proportional to measurement quality. We leverage this to provide interpretation
in terms of random walks and visualization tools for these bounds in both the
anchored and anchor-free scenarios. Similar bounds previously established were
limited to rotations in the plane and Gaussian-like noise
Activity recognition from videos with parallel hypergraph matching on GPUs
In this paper, we propose a method for activity recognition from videos based
on sparse local features and hypergraph matching. We benefit from special
properties of the temporal domain in the data to derive a sequential and fast
graph matching algorithm for GPUs.
Traditionally, graphs and hypergraphs are frequently used to recognize
complex and often non-rigid patterns in computer vision, either through graph
matching or point-set matching with graphs. Most formulations resort to the
minimization of a difficult discrete energy function mixing geometric or
structural terms with data attached terms involving appearance features.
Traditional methods solve this minimization problem approximately, for instance
with spectral techniques.
In this work, instead of solving the problem approximatively, the exact
solution for the optimal assignment is calculated in parallel on GPUs. The
graphical structure is simplified and regularized, which allows to derive an
efficient recursive minimization algorithm. The algorithm distributes
subproblems over the calculation units of a GPU, which solves them in parallel,
allowing the system to run faster than real-time on medium-end GPUs
Estimation under group actions: recovering orbits from invariants
Motivated by geometric problems in signal processing, computer vision, and
structural biology, we study a class of orbit recovery problems where we
observe very noisy copies of an unknown signal, each acted upon by a random
element of some group (such as Z/p or SO(3)). The goal is to recover the orbit
of the signal under the group action in the high-noise regime. This generalizes
problems of interest such as multi-reference alignment (MRA) and the
reconstruction problem in cryo-electron microscopy (cryo-EM). We obtain
matching lower and upper bounds on the sample complexity of these problems in
high generality, showing that the statistical difficulty is intricately
determined by the invariant theory of the underlying symmetry group.
In particular, we determine that for cryo-EM with noise variance
and uniform viewing directions, the number of samples required scales as
. We match this bound with a novel algorithm for ab initio
reconstruction in cryo-EM, based on invariant features of degree at most 3. We
further discuss how to recover multiple molecular structures from heterogeneous
cryo-EM samples.Comment: 54 pages. This version contains a number of new result
Chorusing, synchrony, and the evolutionary functions of rhythm
A central goal of biomusicology is to understand the biological basis of human musicality. One approach to this problem has been to compare core components of human musicality (relative pitch perception, entrainment, etc.) with similar capacities in other animal species. Here we extend and clarify this comparative approach with respect to rhythm. First, whereas most comparisons between human music and animal acoustic behavior have focused on spectral properties (melody and harmony), we argue for the central importance of temporal properties, and propose that this domain is ripe for further comparative research. Second, whereas most rhythm research in non-human animals has examined animal timing in isolation, we consider how chorusing dynamics can shape individual timing, as in human music and dance, arguing that group behavior is key to understanding the adaptive functions of rhythm. To illustrate the interdependence between individual and chorusing dynamics, we present a computational model of chorusing agents relating individual call timing with synchronous group behavior. Third, we distinguish and clarify mechanistic and functional explanations of rhythmic phenomena, often conflated in the literature, arguing that this distinction is key for understanding the evolution of musicality. Fourth, we expand biomusicological discussions beyond the species typically considered, providing an overview of chorusing and rhythmic behavior across a broad range of taxa (orthopterans, fireflies, frogs, birds, and primates). Finally, we propose an “Evolving Signal Timing” hypothesis, suggesting that similarities between timing abilities in biological species will be based on comparable chorusing behaviors. We conclude that the comparative study of chorusing species can provide important insights into the adaptive function(s) of rhythmic behavior in our “proto-musical” primate ancestors, and thus inform our understanding of the biology and evolution of rhythm in human music and language
Using Computational Agents to Design Participatory Social Simulations
In social science, the role of stakeholders is increasing in the development and use of simulation models. Their participation in the design of agent-based models (ABMs) has widely been considered as an efficient solution to the validation of this particular type of model. Traditionally, "agents" (as basic model elements) have not been concerned with stakeholders directly but via designers or role-playing games (RPGs). In this paper, we intend to bridge this gap by introducing computational or software agents, implemented from an initial ABM, into a new kind of RPG, mediated by computers, so that these agents can interact with stakeholders. This interaction can help not only to elicit stakeholders' informal knowledge or unpredicted behaviours, but also to control stakeholders' focus during the games. We therefore formalize a general participatory design method using software agents, and illustrate it by describing our experience in a project aimed at developing agent-based social simulations in the field of air traffic management.Participatory Social Simulations, Agent-Based Social Simulations, Computational Agents, Role-Playing Games, Artificial Maieutics, User-Centered Design
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