Publications related to Reinforcement

Related publications (29)

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Friedhelm Christoph Hummel, Takuya Morishita, Maximilian Jonas Wessel, Elena Beanato, Traian Popa, Pierre Theopistos Vassiliadis, Fabienne Windel, Esra Neufeld

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...

Nature Portfolio2024

Unveiling the complexity of learning and decision-making

Wei-Hsiang Lin

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

EPFL2024

Simulating intra-household interactions for in- and out-of-home activity scheduling

Michel Bierlaire, Timothy Michael Hillel, Negar Rezvany

Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly base ...

Pergamon-Elsevier Science Ltd2023

Mechanisms underlying reinforcement learning of motor skills

Pierre Theopistos Vassiliadis

Motor learning allows animals, including human beings, to acquire skills that are es-sential for efficient interactions with the environment. This ability to learn new motor skills is of great practical relevance for daily-life activities (such as when lea ...

EPFL2023

Dynamic indoor thermal environment using Reinforcement Learning-based controls: Opportunities and challenges

Dolaana Khovalyg, Arnab Chatterjee

Currently, the indoor thermal environment in many buildings is controlled by conventional control techniques that maintain the indoor temperature within a prescribed deadband. The latest research provides evidence that more dynamic variations of the indoor ...

2023

On the role of energy infrastructure in the energy transition. Case study of an energy independent and CO2 neutral energy system for Switzerland

François Maréchal, Sidi-Rachid Cherkaoui, Jonas Schnidrig, Manuele Domenico Margni, Yasmine Maria Calisesi Arzner

The transition towards renewable energy is leading to an important strain on the energy grids. The question of designing and deploying renewable energy technologies in symbiosis with existing grids and infrastructure is arising. While current energy system ...

2023

Reinforcement learning approach to control an inverted pendulum: A general framework for educational purposes

Jesus Sanchez Rodriguez

Machine learning is often cited as a new paradigm in control theory, but is also often viewed as empirical and less intuitive for students than classical model-based methods. This is particularly the case for reinforcement learning, an approach that does n ...

PUBLIC LIBRARY SCIENCE2023

A striatal circuit balances learned fear in the presence and absence of sensory cues

Ralf Schneggenburger, Olexiy Kochubey, Michael Kintscher

During fear learning, defensive behaviors like freezing need to be finely balanced in the presence or absence of threat-predicting cues (conditioned stimulus, CS). Nevertheless, the circuits underlying such balancing are largely unknown. Here, we investiga ...

eLIFE SCIENCES PUBL LTD2023

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Colin Neil Jones, Loris Di Natale

Model-free Reinforcement Learning (RL) generally suffers from poor sample complexity, mostly due to the need to exhaustively explore the state-action space to find well-performing policies. On the other hand, we postulate that expert knowledge of the syste ...

2023

Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units

Olga Fink

This paper proposes a safe reinforcement learning algorithm for generation bidding decisions and unit maintenance scheduling in a competitive electricity market environment. In this problem, each unit aims to find a bidding strategy that maximizes its reve ...

2023

Plasticity of sensory representations in the posterior insular cortex during fear learning

Denys Osypenko

Aversively-motivated associative learning allows animals to avoid harm and thus ensures survival. Aversive learning can be studied by the fear learning paradigm, in which an innocuous sensory stimulus like a tone (conditioned stimulus, CS), acquires a nega ...

EPFL2023

Striatal Dopamine Signals and Reward Learning

Carl Petersen, Sylvain Crochet, Yanqi Liu, Parviz Ghaderi, Christos Sourmpis, Pol Bech Vilaseca, Mauro Pulin, Anthony Pierre Robert Renard, Meriam Malekzadeh, Robin François Virginien Dard

We are constantly bombarded by sensory information and constantly making decisions on how to act. In order to optimally adapt behavior, we must judge which sequences of sensory inputs and actions lead to successful outcomes in specific circumstances. Neuro ...

Oxford Univ Press2023

Influence of sustained loading on resistance and deformation capacity of reinforced concrete members in compression

Aurelio Muttoni, Miguel Fernández Ruiz, Xhemsi Malja

As acknowledged explicitly or implicitly in most of current design codes, a high level of sustained loading has a detrimental effect on the concrete compressive strength. However, its beneficial effect in terms of deformation capacity is neglected in most ...

ERNST & SOHN2022

An insular cortex - lateral amygdala network in fear learning

Shriya Palchaudhuri

Animals are capable of evaluating sensory cues for possible threats and adapting their behaviours accordingly. Fear learning is an evolutionarily conserved behaviour crucial for animal survival, during which sensory percepts with a negative reinforcing qua ...

EPFL2022

Reward timing matters in motor learning

Pierre Theopistos Vassiliadis

Reward timing, that is, the delay after which reward is delivered following an action is known to strongly influence reinforcement learning. Here, we asked if reward timing could also modulate how people learn and consolidate new motor skills. In 60 health ...

CELL PRESS2022

Experimental investigation of dowel action using advanced measurement techniques

Aurelio Muttoni, Marko Pejatovic

Existing shear-cracked structures need to be reliably verified in order to avoid redundant interventions. Code provisions often raise shear safety and/or fatigue life concerns of the reinforcement subjected to stress concentrations due to cyclic dowel acti ...

2022

Reinforcement Learning for the occupant-centric operation of building energy systems: Theoretical and experimental investigations

Amirreza Heidari

Occupant behavior, defined as the presence and energy-related actions of occupants, is today known as a key driver of building energy use. Closing the gap between what is provided by building energy systems and what is actually needed by occupants requires ...

EPFL2022

Identifiability and Generalizability from Multiple Experts in Inverse Reinforcement Learning

Volkan Cevher, Luca Viano, Paul Thierry Yves Rolland, Boris Nikolov

While Reinforcement Learning (RL) aims to train an agent from a reward function in a given environment, Inverse Reinforcement Learning (IRL) seeks to recover the reward function from observing an expert’s behavior. It is well known that, in general, variou ...

2022

Bio-inspired Reflex System for Learning Visual Information for Resilient Robotic Manipulation

Josephine Anna Eleanor Hughes, Kai Christian Junge

Humans have an incredible sense of self-preservation that is both instilled, and also learned through experience. One system which contributes to this is the pain and reflex system which both minimizes damage through involuntary reflex ac- tions and also s ...

2022