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arxiv.org

A system of non-tradable credits that flow between individuals like karma, hence proposed under that name, is a mechanism for repeated resource allocation that comes with attractive efficiency and fairness properties, in theory. In this study, we test karma in an online experiment in which human subjects repeatedly compete for a resource with time-varying and stochastic individual preferences or urgency to acquire the resource. We confirm that karma has significant and sustained welfare benefits even in a population with no prior training. We identify mechanism usage in contexts with sporadic high urgency, more so than with frequent moderate urgency, and implemented as a simple (binary) karma bidding scheme as particularly effective for welfare improvements: relatively larger aggregate efficiency gains are realized that are (almost) Pareto superior. These findings provide guidance for further testing and for future implementation plans of such mechanisms in the real world.

domino.ai

RevX covers hot topics from Generative AI and advanced machine learning algorithms to data visualization techniques. Now you can watch the sessions on demand.

harness.io

Harness is a unified, end-to-end AI software delivery platform to manage the SDLC using purpose-built AI agents.

amplitude.com

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optimizely.com

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deeprlcourse.github.io

This page provides an in-depth exploration of policy-based methods in reinforcement learning, focusing on their theoretical foundations, practical implementations, and advantages over value-based methods. Topics include policy gradient theorem, variance reduction techniques, REINFORCE algorithm, actor-critic methods, and their applications in continuous action spaces. The content is enriched with mathematical proofs, examples, and visual aids to enhance understanding.

optml.mit.edu

suvrit sra's professional webpage