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Game Theory

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Recent Advances in General Game Playing.

TheScientificWorldJournal
The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. ...

Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley.

Cognition
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...

Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective.

IEEE transactions on neural networks and learning systems
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...

Competition among networks highlights the power of the weak.

Nature communications
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...

A mathematical model for the two-learners problem.

Journal of neural engineering
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.

Cultural Transmission and Evolution of Melodic Structures in Multi-generational Signaling Games.

Artificial life
It has been proposed that languages evolve by adapting to the perceptual and cognitive constraints of the human brain, developing, in the course of cultural transmission, structural regularities that maximize or optimize learnability and ease of proc...

Emergent Solutions to High-Dimensional Multitask Reinforcement Learning.

Evolutionary computation
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...

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
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...

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
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...

Deep learning on chaos game representation for proteins.

Bioinformatics (Oxford, England)
MOTIVATION: Classification of protein sequences is one big task in bioinformatics and has many applications. Different machine learning methods exist and are applied on these problems, such as support vector machines (SVM), random forests (RF) and ne...