The University of Southampton
University of Southampton Institutional Repository

Extended Markov Tracking with Ensemble Actions

Extended Markov Tracking with Ensemble Actions
Extended Markov Tracking with Ensemble Actions
In this paper we extend the control methodology based on Extended Markov Tracking (EMT) by providing the control algorithm with capabilities to calibrate and even partially reconstruct the environment's model. This enables us to resolve the problem of performance deterioration due to model incoherence, a negative problem in all model based control methods. The new algorithm, Ensemble Actions EMT (EA-EMT), utilises the initial environment model as a library of state transition functions and applies a variation of prediction with experts to assemble and calibrate a revised model. By so doing, this is the first control algorithm that enables on-line adaptation within the Dynamics Based Control (DBC) framework. In our experiments, we performed a range of tests with increasing model incoherence induced by three types of exogenous environment perturbations: catastrophic, periodic and deviating. The results show that EA-EMT resolved model incoherence and significantly outperformed the best currently available DBC solution by up to $95\%$.
Rabinovich, Zinovi
573422bf-523d-466b-a047-7a92917102e7
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Rabinovich, Zinovi
573422bf-523d-466b-a047-7a92917102e7
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Rabinovich, Zinovi and Jennings, Nick (2009) Extended Markov Tracking with Ensemble Actions. International Workshop on Hybrid Control of Autonomous Systems.

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper we extend the control methodology based on Extended Markov Tracking (EMT) by providing the control algorithm with capabilities to calibrate and even partially reconstruct the environment's model. This enables us to resolve the problem of performance deterioration due to model incoherence, a negative problem in all model based control methods. The new algorithm, Ensemble Actions EMT (EA-EMT), utilises the initial environment model as a library of state transition functions and applies a variation of prediction with experts to assemble and calibrate a revised model. By so doing, this is the first control algorithm that enables on-line adaptation within the Dynamics Based Control (DBC) framework. In our experiments, we performed a range of tests with increasing model incoherence induced by three types of exogenous environment perturbations: catastrophic, periodic and deviating. The results show that EA-EMT resolved model incoherence and significantly outperformed the best currently available DBC solution by up to $95\%$.

Text
hycas.pdf - Author's Original
Download (143kB)

More information

Published date: 13 July 2009
Venue - Dates: International Workshop on Hybrid Control of Autonomous Systems, 2009-07-13
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 267337
URI: http://eprints.soton.ac.uk/id/eprint/267337
PURE UUID: 869d81f5-adca-4961-adcd-725641df75f9

Catalogue record

Date deposited: 07 May 2009 11:55
Last modified: 14 Mar 2024 08:48

Export record

Contributors

Author: Zinovi Rabinovich
Author: Nick Jennings

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×