his.sePublikationer
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
The Kaizen Agent: A self-driving car continuously learns by imagination
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi. (Interaction Lab (ILAB))ORCID-id: 0000-0003-0093-3655
2019 (Engelska)Rapport (Övrigt vetenskapligt)
Abstract [en]

For an agent to autonomously interact in a real world environment, it needs tolearn how to behave in the different scenarios that it may face. There are differentapproaches of modeling an artificial agent with interactive capabilities. Oneapproach is providing the agent with knowledge beforehand. Another approachis to let the agent learn from data and interaction. A well-known techniques ofthe former approach is supervised learning. In this approach, data is collected,labeled and provided to train the network as pre-defined input and correct outputas a training set. This requires data to be available beforehand. In a realworld environment however, it is difficult to determine all possible interactionsand provide the correct response to each. The agent thus needs to be able tolearn by itself from the environment to figure out the best reaction in each situation.To facilitate this, the agent needs to be able to sense the environment,make decisions and react back to the environment. The agent repeats this tryingdifferent decisions. To learn from these trials, the agent needs to accumulate oldexperiences, learn and adjust its knowledge and develop progressively after eachinteraction. However, in many applications, experiencing various actions in differentscenarios is difficult, dangerous or even impossible. The agent thereforeneeds an experimental environment where it can safely explore the possibilities,learn from experiences and develop new skills.This research aims to develop a methodology to build an interactive learningagent that can improve its learning performance progressively and perform wellin real world environments. The agent follows the Japanese concept Kaizenwhich refers to activities that continuously improve all functions. It meansstriving for continuous improvement and not radically changing processes. Thecontribution of this research is first to model and develop this agent so thatit can acquire new knowledge based on existing knowledge without negativelyaffecting the old knowledge and skills. Secondly, this research aims to developa novel method to systematically generate synthetic scenarios that contributesto its learning performance.This proposal consists of the background of artificial cognitive systems, acomparison of the theories and approaches in artificial cognitive systems fordeveloping a learning interactive system, and a review of the state of the artin reinforcement learning. Imagination-based learning is discussed and the purposesof imagination are defined. Imagination for creation is used as a scenariogenerator for practicing new skills without the necessity to try them all in thereal world. The research proposal results in the research questions and objectivesto be investigated as well as an outline of the methodology.

Ort, förlag, år, upplaga, sidor
2019. , s. 33
Nationell ämneskategori
Annan elektroteknik och elektronik
Forskningsämne
Interaction Lab (ILAB)
Identifikatorer
URN: urn:nbn:se:his:diva-18176OAI: oai:DiVA.org:his-18176DiVA, id: diva2:1388947
Anmärkning

Research proposal, PhD programme, University of Skövde

Tillgänglig från: 2020-01-28 Skapad: 2020-01-28 Senast uppdaterad: 2020-02-24Bibliografiskt granskad

Open Access i DiVA

The Kaizen Agent- A self-driving car continuously learns by imagination(1056 kB)15 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 1056 kBChecksumma SHA-512
5cdbc6e470eae0e1a595487e3a7ce6dbd0e97df42006743cd625c63a9b67f97094adfa01b0be7ccd4b742aea7bdf145bc7a58400b021b4af1067c1443465de44
Typ fulltextMimetyp application/pdf

Personposter BETA

Mahmoud, Sara

Sök vidare i DiVA

Av författaren/redaktören
Mahmoud, Sara
Av organisationen
Institutionen för informationsteknologiForskningsmiljön Informationsteknologi
Annan elektroteknik och elektronik

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 15 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

urn-nbn

Altmetricpoäng

urn-nbn
Totalt: 109 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf