Search

Summary

An overview of the basic concepts and components of likelihood-based modelling and introduces the process of maximizing a likelihood.We show that the OLS model can be derived in a likelihood framework.

The benefit obtained by a selfish robot by cheating in a real multirobotic system can be represented by the random variable Xn,q: the number of cheating interactions needed before all the members in a cooperative team of robots, playing a TIT FOR TAT strategy, recognize the selfish robot. Stability of cooperation depends on the ratio between the benefit obtained by selfish and cooperative robots. In this paper, we establish the probability model for Xn,q. If the values of the parameters n and q are known, then this model allows us to make predictions about the stability of cooperation. Moreover, if these parameters are modifiable, it is possible to tune them to guarantee the viability of cooperation.

An explicit formula is derived for the variance normalizing constant in the central limit theorem for chain-dependent processes. As an application to meteorology, a specific chain-dependent process is proposed as a probabilistic model for the sequence of daily amounts of precipitation. This model is a generalization of the commonly used Markov chain model for the occurrence of precipitation.

Search Results

Refine search

Refine search

Actions for selected content:

3 results

1 - Introduction to Maximum Likelihood

Summary

Probability distribution of the number of deceits in collective robotics

An application of chain-dependent processes to meteorology

Search Results

Refine search

Refine search

Actions for selected content:

Save Search

3 results

1 - Introduction to Maximum Likelihood

Summary

Probability distribution of the number of deceits in collective robotics

An application of chain-dependent processes to meteorology