The Interacting Multiple Models Algorithm with State-Dependent Value Assignment

The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and th...

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Main Author: Rastgoufard, Rastin
Format: Others
Published: ScholarWorks@UNO 2012
Subjects:
IMM
Online Access:http://scholarworks.uno.edu/td/1477
http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=2421&context=td
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spelling ndltd-uno.edu-oai-scholarworks.uno.edu-td-24212016-10-21T17:06:21Z The Interacting Multiple Models Algorithm with State-Dependent Value Assignment Rastgoufard, Rastin The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and then we use a game's player-controlled trajectories as ground truths to compare the normal IMM algorithm to versions with our proposed modifications. The two methods involve modifying the model probabilities in the update step and modifying the transition probability matrix in the mixing step based on the assigned values of different target states. The state-dependent value assignment modifications are shown experimentally to perform better than the normal IMM algorithm in both estimating the target's current state and predicting the target's next state. 2012-05-18T07:00:00Z text application/pdf http://scholarworks.uno.edu/td/1477 http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=2421&context=td University of New Orleans Theses and Dissertations ScholarWorks@UNO IMM state-dependent constraints penalty function waypoints obstacles Artificial Intelligence and Robotics Signal Processing Statistical Models
collection NDLTD
format Others
sources NDLTD
topic IMM
state-dependent
constraints
penalty function
waypoints
obstacles
Artificial Intelligence and Robotics
Signal Processing
Statistical Models
spellingShingle IMM
state-dependent
constraints
penalty function
waypoints
obstacles
Artificial Intelligence and Robotics
Signal Processing
Statistical Models
Rastgoufard, Rastin
The Interacting Multiple Models Algorithm with State-Dependent Value Assignment
description The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and then we use a game's player-controlled trajectories as ground truths to compare the normal IMM algorithm to versions with our proposed modifications. The two methods involve modifying the model probabilities in the update step and modifying the transition probability matrix in the mixing step based on the assigned values of different target states. The state-dependent value assignment modifications are shown experimentally to perform better than the normal IMM algorithm in both estimating the target's current state and predicting the target's next state.
author Rastgoufard, Rastin
author_facet Rastgoufard, Rastin
author_sort Rastgoufard, Rastin
title The Interacting Multiple Models Algorithm with State-Dependent Value Assignment
title_short The Interacting Multiple Models Algorithm with State-Dependent Value Assignment
title_full The Interacting Multiple Models Algorithm with State-Dependent Value Assignment
title_fullStr The Interacting Multiple Models Algorithm with State-Dependent Value Assignment
title_full_unstemmed The Interacting Multiple Models Algorithm with State-Dependent Value Assignment
title_sort interacting multiple models algorithm with state-dependent value assignment
publisher ScholarWorks@UNO
publishDate 2012
url http://scholarworks.uno.edu/td/1477
http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=2421&context=td
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