Stimulus sampling as an exploration mechanism for fast reinforcement learning
Related publications (113)
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In timing-based neural codes, neurons have to emit action potentials at precise moments in time. We use a supervised learning paradigm to derive a synaptic update rule that optimizes by gradient ascent the likelihood of postsynaptic firing at one or severa ...
We compare improvement through training in vernier acuity under different feedback conditions in order to clarify the role of feedback during learning of a perceptual task and to test different (neural network) models of perceptual learning. Improvement of ...
This paper presents a methodology for extracting meaningful synchronous structures from multi-modal signals. Simultaneous processing of multi-modal data can reveal information that is unavailable when handling the sources separately. However, in natural hi ...
In this paper, we extend the Hopfield Associative Memory for storing multiple sequences of varying duration. We apply the model for learning, recognizing and encoding a set of human gestures. We measure systematically the performance of the model against n ...
We study spatial learning and navigation for autonomous agents. A state space representation is constructed by unsupervised Hebbian learning during exploration. As a result of learning, a representation of the continuous two-dimensional (2-D) manifold in t ...
Institute of Electrical and Electronics Engineers2004
We investigated the roles of feedback and attention in training a vernier discrimination task as an example of perceptual learning. Human learning even of simple stimuli, such as verniers, relies on more complex mechanisms than previously expected--ruling ...
We investigate the influence of biased feedback on decision and learning processes in a vernier discrimination task. Subjects adjust their decision criteria and hence their responses according to biased external feedback. However, they do not use learning ...
We propose a novel network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, based on biological observations of synaptic plasticity. The model is furt ...
The Swiss Federal Institute of Technology in Lausanne (EPFL) has successfully integrated the Bologna reform process that standardizes the Bachelor and Master programmes across Europe. This reform particularly affects the curriculum offered by the EPFL scho ...
In [8] Yamauchi and Beer explored the abilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement-learning like abilities. The investigated tasks were generation and learning of short bit sequences. This "learning'' came about ...