AIMC Topic: Game Theory

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Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game.

Neural networks : the official journal of the International Neural Network Society Aug 25, 2019
Deep Reinforcement Learning (RL) demonstrates excellent performance on tasks that can be solved by trained policy. It plays a dominant role among cutting-edge machine learning approaches using multi-layer Neural networks (NNs). At the same time, Deep...
Machine Learning Game Theory
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Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases.

Artificial intelligence in medicine Jul 23, 2019
In order to gain insight into oligogenic disorders, understanding those involving bi-locus variant combinations appears to be key. In prior work, we showed that features at multiple biological scales can already be used to discriminate among two type...
Game Theory Multifactorial Inheritance Humans Machine Learning Genetic Predisposition to Disease Decision Trees
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Superhuman AI for multiplayer poker.

Science (New York, N.Y.) Jul 11, 2019
In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such b...
Humans Artificial Intelligence Game Theory Games, Recreational
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Optimization of sampling intervals for tracking control of nonlinear systems: A game theoretic approach.

Neural networks : the official journal of the International Neural Network Society Mar 8, 2019
This paper presents a near optimal adaptive event-based sampling scheme for tracking control of an affine nonlinear continuous-time system. A zero-sum game approach is proposed by introducing a novel performance index. The optimal value function, i.e...
Neural Networks, Computer Nonlinear Dynamics Feedback Game Theory
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Shared Nearest-Neighbor Quantum Game-Based Attribute Reduction With Hierarchical Coevolutionary Spark and Its Application in Consistent Segmentation of Neonatal Cerebral Cortical Surfaces.

IEEE transactions on neural networks and learning systems Nov 6, 2018
The unprecedented increase in data volume has become a severe challenge for conventional patterns of data mining and learning systems tasked with handling big data. The recently introduced Spark platform is a new processing method for big data analys...
Algorithms Infant, Newborn Neural Networks, Computer Game Theory Cluster Analysis Cerebral Cortex Humans
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Emergent Solutions to High-Dimensional Multitask Reinforcement Learning.

Evolutionary computation Jun 22, 2018
Algorithms that learn through environmental interaction and delayed rewards, or reinforcement learning (RL), increasingly face the challenge of scaling to dynamic, high-dimensional, and partially observable environments. Significant attention is bein...
Cooperative Behavior Reinforcement, Psychology Game Theory Learning Models, Psychological Algorithms Neural Networks, Computer
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A mathematical model for the two-learners problem.

Journal of neural engineering Feb 22, 2017
OBJECTIVE: We present the first generic theoretical formulation of the co-adaptive learning problem and give a simple example of two interacting linear learning systems, a human and a machine.
Linear Models Humans Man-Machine Systems Machine Learning Game Theory Animals Computer Simulation Models, Neurological Learning
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Competition among networks highlights the power of the weak.

Nature communications Nov 14, 2016
The unpreventable connections between real networked systems have recently called for an examination of percolation, diffusion or synchronization phenomena in multilayer networks. Here we use network science and game theory to explore interactions in...
Computer Communication Networks Game Theory Algorithms Models, Theoretical Humans Neural Networks, Computer
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Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective.

IEEE transactions on neural networks and learning systems Jan 21, 2016
This paper considers cooperative kinematic control of multiple manipulators using distributed recurrent neural networks and provides a tractable way to extend existing results on individual manipulator control using recurrent neural networks to the s...
Game Theory Neural Networks, Computer Cooperative Behavior
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Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley.

Cognition Sep 21, 2015
Android robots are entering human social life. However, human-robot interactions may be complicated by a hypothetical Uncanny Valley (UV) in which imperfect human-likeness provokes dislike. Previous investigations using unnaturally blended images rep...
Game Theory Social Perception Facial Recognition Male Trust Robotics Female Humans Facial Expression Adult
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