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Found 10 papers, 2 papers with code
Mathematics of multi-agent learning systems at the interface of game theory and artificial intelligence
The former focuses on the evolution of behaviors (or strategies) in a population, where individuals interact with others and update their strategies based on imitation (or social learning).
Reinforcement Learning Jazz Improvisation: When Music Meets Game Theory
Live performances of music are always charming, with the unpredictability of improvisation due to the dynamic between musicians and interactions with the audience.
Social Learning and the Exploration-Exploitation Tradeoff
In this work, we investigate the balance between exploration and exploitation in changing environments by thinking of exploration as mutation in a trait space with a varying fitness function.
Population heterogeneity in vaccine coverage impacts epidemic thresholds and bifurcation dynamics
For vaccine-preventable diseases, outstanding issues like vaccine hesitancy and availability of vaccines further lead to nonuniform coverage among groups, not to mention the efficacy of vaccines and the mixing pattern varying from one group to another.
Evolutionary games and spatial periodicity
We establish a theoretical framework to address evolutionary dynamics of spatial games under strong selection.
The Point of No Return: Evolution of Excess Mutation Rate is Possible Even for Simple Mutation Models
This work uses adaptive dynamics to study the evolution of mutation rate, and the replicator-mutator equation to model trait evolution.
Immune checkpoint therapy modeling of PD-1/PD-L1 blockades reveals subtle difference in their response dynamics and potential synergy in combination
Immune checkpoint therapy is one of the most promising immunotherapeutic methods that are likely able to give rise to durable treatment response for various cancer types.
Random Choices can Facilitate the Solving of Collective Network Coloring Problems by Artificial Agents
Global coordination is required to solve a wide variety of challenging collective action problems from network colorings to the tragedy of the commons.
Physics and Society
Sentiment-Based Prediction of Alternative Cryptocurrency Price Fluctuations Using Gradient Boosting Tree Model
These two indices, alongside the raw summations of positive, negative, and neutral sentiment were juxtaposed to $\sim 400$ data points of hourly pricing data to train an Extreme Gradient Boosting Regression Tree Model.
Physics and Society Computational Finance
Risk-Aware Multi-Armed Bandit Problem with Application to Portfolio Selection
Sequential portfolio selection has attracted increasing interests in the machine learning and quantitative finance communities in recent years.
Portfolio Management
