2,974 research outputs found
Grounding semantics in robots for Visual Question Answering
In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning
The evolution of case grammar
"There are few linguistic phenomena that have seduced linguists so skillfully as grammatical case has done. Ever since Panini (4th Century BC), case has claimed a central role in linguistic theory and continues to do so today. However, despite centuries worth of research, case has yet to reveal its most important secrets.
This book offers breakthrough explanations for the understanding of case through agent-based experiments in cultural language evolution. The experiments demonstrate that case systems may emerge because they have a selective advantage for communication: they reduce the cognitive effort that listeners need for semantic interpretation, while at the same time limiting the cognitive resources required for doing so.
Prospects for Declarative Mathematical Modeling of Complex Biological Systems
Declarative modeling uses symbolic expressions to represent models. With such
expressions one can formalize high-level mathematical computations on models
that would be difficult or impossible to perform directly on a lower-level
simulation program, in a general-purpose programming language. Examples of such
computations on models include model analysis, relatively general-purpose
model-reduction maps, and the initial phases of model implementation, all of
which should preserve or approximate the mathematical semantics of a complex
biological model. The potential advantages are particularly relevant in the
case of developmental modeling, wherein complex spatial structures exhibit
dynamics at molecular, cellular, and organogenic levels to relate genotype to
multicellular phenotype. Multiscale modeling can benefit from both the
expressive power of declarative modeling languages and the application of model
reduction methods to link models across scale. Based on previous work, here we
define declarative modeling of complex biological systems by defining the
operator algebra semantics of an increasingly powerful series of declarative
modeling languages including reaction-like dynamics of parameterized and
extended objects; we define semantics-preserving implementation and
semantics-approximating model reduction transformations; and we outline a
"meta-hierarchy" for organizing declarative models and the mathematical methods
that can fruitfully manipulate them
Behavior finding: Morphogenetic Designs Shaped by Function
Evolution has shaped an incredible diversity of multicellular living organisms, whose complex forms are self-made through a robust developmental process. This fundamental combination of biological evolution and development has served as an inspiration for novel engineering design methodologies, with the goal to overcome the scalability problems suffered by classical top-down approaches. Top-down methodologies are based on the manual decomposition of the design into modular, independent subunits. In contrast, recent computational morphogenetic techniques have shown that they were able to automatically generate truly complex innovative designs. Algorithms based on evolutionary computation and artificial development have been proposed to automatically design both the structures, within certain constraints, and the controllers that optimize their function. However, the driving force of biological evolution does not resemble an enumeration of design requirements, but much rather relies on the interaction of organisms within the environment. Similarly, controllers do not evolve nor develop separately, but are woven into the organism’s morphology. In this chapter, we discuss evolutionary morphogenetic algorithms inspired by these important aspects of biological evolution. The proposed methodologies could contribute to the automation of processes that design “organic” structures, whose morphologies and controllers are intended to solve a functional problem. The performance of the algorithms is tested on a class of optimization problems that we call behavior-finding. These challenges are not explicitly based on morphology or controller constraints, but only on the solving abilities and efficacy of the design. Our results show that morphogenetic algorithms are well suited to behavior-finding
The evolution of case grammar
There are few linguistic phenomena that have seduced linguists so skillfully as grammatical case has done. Ever since Panini (4th Century BC), case has claimed a central role in linguistic theory and continues to do so today. However, despite centuries worth of research, case has yet to reveal its most important secrets. This book offers breakthrough explanations for the understanding of case through agent-based experiments in cultural language evolution. The experiments demonstrate that case systems may emerge because they have a selective advantage for communication: they reduce the cognitive effort that listeners need for semantic interpretation, while at the same time limiting the cognitive resources required for doing so
The evolution of case grammar
There are few linguistic phenomena that have seduced linguists so skillfully as grammatical case has done. Ever since Panini (4th Century BC), case has claimed a central role in linguistic theory and continues to do so today. However, despite centuries worth of research, case has yet to reveal its most important secrets. This book offers breakthrough explanations for the understanding of case through agent-based experiments in cultural language evolution. The experiments demonstrate that case systems may emerge because they have a selective advantage for communication: they reduce the cognitive effort that listeners need for semantic interpretation, while at the same time limiting the cognitive resources required for doing so
The evolution of case grammar
There are few linguistic phenomena that have seduced linguists so skillfully as grammatical case has done. Ever since Panini (4th Century BC), case has claimed a central role in linguistic theory and continues to do so today. However, despite centuries worth of research, case has yet to reveal its most important secrets. This book offers breakthrough explanations for the understanding of case through agent-based experiments in cultural language evolution. The experiments demonstrate that case systems may emerge because they have a selective advantage for communication: they reduce the cognitive effort that listeners need for semantic interpretation, while at the same time limiting the cognitive resources required for doing so
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