Agnar Aamodt
Bakgrunn og aktiviteter
Professor i informatikk og kunstig intelligens.
Tilknyttet Norwegian Open AI Lab.
Forskningsområde
Hoved-forskningsområdet er kunstig intelligens, og spesielt metoder for data-analyse og erfaringsbasert støtte til folks problemløsing og læring. Spesielle områder er:
- Metoder som fanger opp og gjenbruker menneskelig erfaringer,
og spesielt case-basert resonnering kombinert med generell kunnskap - Maskinlæring og dataanalyse
- Kunnskapsmodellering og -representasjon
- Kognisjonsvitenskap
- Beslutningsstøtte-systemer
Anvendelsesområder i fokus inkluderer medisin og helse, fiskeoppdrett, petroleumsteknologi, søk og redning.
Forskningsgruppe: Data and Artificial Intelligence
Mer informasjon: www.idi.ntnu.no/~agnar
Vitenskapelig, faglig og kunstnerisk arbeid
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
Tidsskriftspublikasjoner
- (2019) Learning similarity measures from data. Progress in Artificial Intelligence.
- (2019) A spatio-temporal recurrent network for salmon feeding action recognition from underwater videos in aquaculture. Computers and Electronics in Agriculture. vol. 167.
- (2018) Design of a clinician dashboard to facilitate co-decision making in the management of non-specific low back pain. Journal of Intelligent Information Systems.
- (2018) Case based reasoning as a model for cognitive artificial intelligence. Lecture Notes in Computer Science (LNCS). vol. 11156 LNAI.
- (2018) Bayesian-Supported Retrieval in BNCreek: A Knowledge-Intensive Case-Based Reasoning System. Lecture Notes in Computer Science (LNCS). vol. 11156 LNAI.
- (2017) Case-Based Reasoning and the Upswing of AI. Lecture Notes in Computer Science (LNCS). vol. 10339.
- (2017) Diversity of Exercise Plans using Evolutionary Inspired Adaptation. CEUR Workshop Proceedings. vol. 1917.
- (2017) A learning system based on lazy metareasoning. Progress in Artificial Intelligence. vol. 7 (2).
- (2017) Data driven case base construction for prediction of success of marine operations. CEUR Workshop Proceedings. vol. 2028.
- (2017) Diagnosing Root Causes and Generating Graphical Explanations by Integrating Temporal Causal Reasoning and CBR. CEUR Workshop Proceedings. vol. 1815.
- (2017) Evolutionary inspired adaptation of exercise plans for increasing solution variety. Lecture Notes in Computer Science (LNCS). vol. 10339 LNAI.
- (2016) Case Representation and Similarity Assessment in the SELFBACK Decision Support System. Lecture Notes in Computer Science (LNCS). vol. 9969 LNCS.
- (2016) Case representation and similarity assessment in the selfBACK decision support system. CEUR Workshop Proceedings. vol. 1670.
- (2015) Evidence-driven retrieval in textual CBR: Bridging the gap between retrieval and reuse. Lecture Notes in Computer Science (LNCS). vol. 9343.
- (2014) Case-based reasoning for improving traffic flow in urban intersections. Lecture Notes in Computer Science (LNCS). vol. 8765.
- (2014) Integrating human related errors with technical errors to determine causes behind offshore accidents. Safety Science. vol. 63.
- (2014) An overview of case-based reasoning applications in drilling engineering. Artificial Intelligence Review. vol. 41 (3).
- (2013) A real-time decision support system for high cost oil-well drilling operations. The AI Magazine. vol. 34 (1).
- (2013) Detection of Symptoms for Revealing Causes Leading to Drilling Failures. SPE Drilling & Completion. vol. 28 (2).
- (2013) Experience Transfer for Process Improvement. Engineering Applications of Artificial Intelligence. vol. 26 (9).