[PDF] Top 20 Reinforcement Learning applied the games of Poker
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Reinforcement Learning applied the games of Poker
... address the issues found in the Restrict Nash Response approach. The main difference in this approach is that instead of using a single parameter p for choosing which strategy to use for every ... See full document
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Dynamic equilibrium through reinforcement learning
... that the agent perceives the environment, this means that the agent will receive information, in general through sensors, about properties of a physical or virtual ...from the sensors ... See full document
99
Meta-level reasoning in reinforcement learning
... Reinforcement learning is a technique often used to generate an optimal (or near-optimal) agent in a stochastic environment in the absence of knowledge about the reward function ... See full document
61
Techniques for batch reinforcement learning in robotics
... Batch Reinforcement Learning methods are able to learn by processing a fixed in- teraction ...However, the methods can be extended to interleave interaction with the environment with updating ... See full document
200
A Reinforcement Learning Environment for Cooperative Multi-Agent Games: Enhancing Negotiation Skills
... be applied to a multitude of situations, being able to generate a model in different scenarios with good results is very beneficial, as it proves the algorithm useful- ...use of the RL ... See full document
91
Using Reinforcement Learning in the tuning of Central Pattern Generators
... approximation of the entire function (Sutton and Barto ...successfully applied to several applications (Beitelspacher et ...Despite the successful implementations, the calculated ... See full document
125
Automatic WLAN control using reinforcement learning for improved quality of experience
... have the same performance when inferring unobserved data” (Wolpert et ...in the control loop. The first of these is one of the simplest algorithms called MAB that learns ... See full document
200
Reinforcement Learning for Primary care e Appointment Scheduling
... class of methods that have been used for the development of scheduling algorithms in clinical practice comes from the machine learning ...machine learning systems to output ... See full document
116
Poker Learner: Reinforcement Learning Applied to Texas Hold'em Poker
... While games have taken great benefits from AI research – especially for non-human player characters – the field also has taken great interest in ...from the well- defined and easy to understand rules ... See full document
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Deep Reinforcement Learning in Strategic Multi-Agent Games: the case of No-Press Diplomacy
... be applied to a multitude of situations, being able to generate a model in different scenarios with good results is very beneficial, as it proves the algorithm useful- ...use of the RL ... See full document
93
Continuous reinforcement operator applied to resilience in disaster rescue networks
... management. The aim of resilient systems surpasses reducing risks by enabling building systems to return to a nominal situation after being ...multiplicity of functions and actors where individuals, ... See full document
6
Beyond chance? The persistence of performance in online poker.
... bias of an estimated coefficient towards zero as a consequence of measurement error is known as attenuation or regression ...impression of the size of the effect of skill ... See full document
23
A Reinforcement Learning for Train Marshaling Based on the Processing Time Considering Group Layout of Freight Cars
... In the case that several cars can be rearranged without a removal, rearrangements are repeated until all the candidates for rear- rangement requires at least one ...removal, the order of ... See full document
6
Simulation games as tools for integrative dynamic learning: The case of the management course at the University of Algarve
... adapt. Learning provided to people is a key feature for an active response since it implies acquiring knowledge, skills and competencies to cope successfully with different ...digital games support ... See full document
11
Games and simulations in distance learning: the AIDLET Model
... patterns of interaction and communication that are of value to Distance ...Education. Games are often heralded as one remedy for the failure of conventional edu- cation but our ... See full document
21
Game engine for development of pervasive games for learning programming
... with the self-learning about the technologies that were necessary to create an android game in ...Besides, the first task was the render of the ...regards the ... See full document
90
Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex.
... model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint ‘‘forearm’’ to a ...target. Learning was based on a reinforcement mechanism ... See full document
8
Building a poker playing agent based on game logs using supervised learning
... from the Poker Research Group [13] in the University of Alberta, having won several Computer Poker Tournaments [7, 14, 15, 16, 17, ...Most of the group’s published work ... See full document
133
Games Applied to Children with Motor Impairment using the Myo Wearable Device
... context, the objective of this work is to develop and evaluate a game adapted to be used with Myo, a wearable device that allows the control of applications through the recognition ... See full document
14
Adaptive value-at-risk policy optimization: a deep reinforcement learning approach for minimizing the capital charge
... 1995, the Basel Committee on Banking Supervision issued an amendment to the first Basel Accord, Basel ...on the value-at-risk (VaR), as opposed to using the regulator’s predefined ...as ... See full document
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