«stationary environment»
۴۱۲۲ نتیجهSensorimotor priors in non - stationary environments 2 3 Abbreviated Title : Priors in non - stationary environments
24 In the course of its interaction with the world, the human nervous system must constantly estimate 25 various variables in the surrounding environment. Past research indicates that environmental variables 26 may be represented as probabilistic distributions of a priori informa
Flocking in Stationary and Non-stationary Environments: A Novel Communication Strategy for Heading Alignment
We propose a novel communication strategy inspired by explicit signaling mechanisms seen in vertebrates, in order to improve performance of self-organized flocking for a swarm of mobile robots. The communication strategy is used to make the robots match each other’s headings. The
Adaptation in Constant Utility Non-Stationary Environments
Environments that vary over time present a fundamental problem to adaptive systems. Although in the worst case there is no hope of eeective adaptation, some forms environmental variability do provide adaptive opportunities. We consider a broad class of non-stationary environments
A Surprise Triggered Adaptive and Reactive (STAR) Framework for Online Adaptation in Non-stationary Environments
We consider the task of developing an adaptive autonomous agent that can interact with non-stationary environments. Traditional learning approaches such as Reinforcement Learning assume stationary characteristics over the course of the problem, and are therefore unable to learn t
Intrinsically Motivated Acquisition of Modular Slow Features for Humanoids in Continuous and Non-Stationary Environments
A compact information-rich representation of the environment, also called a feature abstraction, can simplify a robot’s task of mapping its raw sensory inputs to useful action sequences. However, in environments that are non-stationary and only partially observable, a single abst
Particle Swarm Optimization in Non-stationary Environments
In this paper, we study the use of particle swarm optimization (PSO) for a class of non-stationary environments. The dynamic problems studied in this work are restricted to one of the possible types of changes that can be produced over the fitness landscape. We propose a hybrid P
The Behavior of Spatially Distributed Evolutionary Algorithms in Non-Stationary Environments
Traditional EAs lose diversity fairly quickly due to the strong selection pressures used to achieve good optimization performance, and thus have diiculty with non-stationary environments ((tness landscapes) unless significant algorithmic changes are made. Decentralized and spatia
Adaptive Variational Particle Filtering in Non-stationary Environments
Online convex optimization is a sequential prediction framework with the goal to track and adapt to the environment through evaluating proper convex loss functions. We study efficient particle filtering methods from the perspective of such framework. We formulate an efficient par
Learning to Negotiate Optimally in Non-stationary Environments
We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal strategy in incomplete information settings. Specifically, an agent learns the optimal strategy to play against an
Learning dynamical systems in a stationary environment
We consider the problem of learning the input–output relation of a dynamical system from noisy data. Our method rests on the use of a smooth simultaneous estimator which generalizes the standard empirical estimator. In a stationary environment, our algorithm is shown to select a