Network formation by reinforcement learning: the long and medium run

نویسندگان

  • Robin Pemantle
  • Brian Skyrms
چکیده

We investigate a simple stochastic model of social network formation by the process of reinforcement learning with discounting of the past. In the limit, for any value of the discounting parameter, small, stable cliques are formed. However, the time it takes to reach the limiting state in which cliques have formed is very sensitive to the discounting parameter. Depending on this value, the limiting result may or may not be a good predictor for realistic observation times.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Improving Long Run Marginal Cost based Pricing along with Extended Benefit Factor method for Revenue Reconciliation of Transmission Network in Restructured Power System

Abstract : There are several methods to cover the costs of a transmission system and distribution networks. These methods are divided into either incremental or marginal approaches, which can be either long-term or short-term. The main difference between the incremental and marginal approach is how to calculate the cost of using the network. In the incremental approach, simulation and in the ma...

متن کامل

Dynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)

In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...

متن کامل

روش نوین قیمت‌گذاری هزینۀ نهایی بلندمدت برای جبران کمبود درآمد شبکۀ انتقال در سیستم قدرت تجدید ساختارشده

The long-run incremental and marginal pricing are two different approaches for pricing transmission and distribution networks usage. The main difference between these two methods is to the way the cost of using the network is calculated. In the former approach, simulations are used, and in the latter, sensitivity analysis methods are used to determine the cost. In this paper, a novel analytical...

متن کامل

A Multiagent Reinforcement Learning algorithm to solve the Community Detection Problem

Community detection is a challenging optimization problem that consists of searching for communities that belong to a network under the assumption that the nodes of the same community share properties that enable the detection of new characteristics or functional relationships in the network. Although there are many algorithms developed for community detection, most of them are unsuitable when ...

متن کامل

An Adaptive Learning Game for Autistic Children using Reinforcement Learning and Fuzzy Logic

This paper, presents an adapted serious game for rating social ability in children with autism spectrum disorder (ASD). The required measurements are obtained by challenges of the proposed serious game. The proposed serious game uses reinforcement learning concepts for being adaptive. It is based on fuzzy logic to evaluate the social ability level of the children with ASD. The game adapts itsel...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Mathematical Social Sciences

دوره 48  شماره 

صفحات  -

تاریخ انتشار 2004