Cargando…

Correction: Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Detalles Bibliográficos
Autores principales:	Vasilaki, Eleni, Frémaux, Nicolas, Urbanczik, Robert, Senn, Walter, Gerstner, Wulfram
Formato:	Texto
Lenguaje:	English
Publicado:	Public Library of Science 2009
Materias:	Correction
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2804701/ http://dx.doi.org/10.1371/annotation/307ea250-3792-4ceb-b905-162d86c96baf

Ejemplares similares

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail
por: Vasilaki, Eleni, et al.
Publicado: (2009)

Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons
por: Frémaux, Nicolas, et al.
Publicado: (2013)

Policy gradient rules for populations of spiking neurons
por: Friedrich, Johannes, et al.
Publicado: (2011)

Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules
por: Frémaux, Nicolas, et al.
Publicado: (2016)

Gradient estimation in dendritic reinforcement learning
por: Schiess, Mathieu, et al.
Publicado: (2012)

Reinforcement learning in dendritic structures
por: Schiess, Mathieu, et al.
Publicado: (2011)

Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression
por: Clopath, Claudia, et al.
Publicado: (2008)

From Hebb Rules to Spike-Timing-Dependent Plasticity: A Personal Account
por: Gerstner, Wulfram
Publicado: (2010)

Modulation of orientation-selective neurons by motion: when additive, when multiplicative?
por: Lüdge, Torsten, et al.
Publicado: (2014)

Stochastic variational learning in recurrent spiking networks
por: Jimenez Rezende, Danilo, et al.
Publicado: (2014)

Voltage and Spike Timing Interact in STDP – A Unified Model
por: Clopath, Claudia, et al.
Publicado: (2010)

Prospective Coding by Spiking Neurons
por: Brea, Johanni, et al.
Publicado: (2016)

Reward-based learning under hardware constraints—using a RISC processor embedded in a neuromorphic substrate
por: Friedmann, Simon, et al.
Publicado: (2013)

Limits to high-speed simulations of spiking neural networks using general-purpose computers
por: Zenke, Friedemann, et al.
Publicado: (2014)

Phenomenological models of synaptic plasticity based on spike timing
por: Morrison, Abigail, et al.
Publicado: (2008)

Spike-timing prediction in cortical neurons with active dendrites
por: Naud, Richard, et al.
Publicado: (2014)

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network
por: Gilra, Aditya, et al.
Publicado: (2017)

A History of Spike-Timing-Dependent Plasticity
por: Markram, Henry, et al.
Publicado: (2011)

General conditions for spiking neurons and plasticity rules to perform independent component analysis
por: Brito, Carlos SN, et al.
Publicado: (2011)

Stabilizing working memory in spiking networks with biologically plausible synaptic dynamics
por: Seeholzer, Alexander, et al.
Publicado: (2014)

Modulation of a decision-making process by spatiotemporal spike patterns decoding: evidence from spike-train metrics analysis and spiking neural network modeling
por: Logiaco, Laureline, et al.
Publicado: (2013)

Multicontact Co-operativity in Spike-Timing–Dependent Structural Plasticity Stabilizes Networks
por: Deger, Moritz, et al.
Publicado: (2018)

Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity
por: Schmutz, Valentin, et al.
Publicado: (2020)

Bridging spiking neuron models and mesoscopic population models - a general theory for neural population dynamics
por: Schwalger, Tilo, et al.
Publicado: (2015)

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size
por: Schwalger, Tilo, et al.
Publicado: (2017)

Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks
por: Zenke, Friedemann, et al.
Publicado: (2015)

On the choice of metric in gradient-based theories of brain function
por: Surace, Simone Carlo, et al.
Publicado: (2020)

Multi-Timescale Memory Dynamics Extend Task Repertoire in a Reinforcement Learning Network With Attention-Gated Memory
por: Martinolli, Marco, et al.
Publicado: (2018)

Natural-gradient learning for spiking neurons
por: Kreutzer, Elena, et al.
Publicado: (2022)

Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations
por: Richmond, Paul, et al.
Publicado: (2011)

Stability of working memory in continuous attractor networks under the control of short-term plasticity
por: Seeholzer, Alexander, et al.
Publicado: (2019)

Inference of neuronal network spike dynamics and topology from calcium imaging data
por: Lütcke, Henry, et al.
Publicado: (2013)

Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo
por: Pawlak, Verena, et al.
Publicado: (2013)

Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models
por: Pozzorini, Christian, et al.
Publicado: (2015)

When shared concept cells support associations: Theory of overlapping memory engrams
por: Gastaldi, Chiara, et al.
Publicado: (2021)

Molecule generation using transformers and policy gradient reinforcement learning
por: Mazuz, Eyal, et al.
Publicado: (2023)

When the Ostrich-Algorithm Fails: Blanking Method Affects Spike Train Statistics
por: Joseph, Kevin, et al.
Publicado: (2018)

Perceptual Learning via Modification of Cortical Top-Down Signals
por: Schäfer, Roland, et al.
Publicado: (2007)

Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning
por: Schäfer, Roland, et al.
Publicado: (2009)

Biologically plausible reinforcement learning of continuous actions
por: Rombouts, Jaldert O, et al.
Publicado: (2013)

Cannot write session to /tmp/vufind_sessions/sess_p46a34td3cvfnugohnkh8lijjp