Johan Källström

455 citations
11 papers · 231 · 1 hit paper · h-index 5

Impact in

Papers in

Johan Källström

11 papers receiving 222 citations

Johan Källström's Hit Papers

A practical guide to multi-objective reinforcement learning and planning 2022 · 172 citations
1720+1+2Years since publication50100150

Peers

Johan Källström
Comparison fields: 5 of 71
  • Artificial Intelligence 83
  • Computational Theory and Mathematics 39
  • Industrial and Manufacturing Engineering 21
  • Software 6
  • Health Informatics 2
Replace Conor F. Hayes with:
Conor F. Hayes Belgium
Mathieu Reymond Belgium
Eugenio Bargiacchi Netherlands
Antonín Komenda Czechia
Kazuteru Miyazaki Japan
Tyler Cody United States
Colin Paterson United Kingdom
Dharmendra Patel India
Gloria Cerasela Crişan Romania
G. Jeyakumar India
Johan Källström relative to Conor F. Hayes Belgium Conor F. Hayes's profile →
Citations per field
00.5×
Conor F. Hayes · 1×
Citations per year

Countries citing papers authored by Johan Källström

Since Specialization
Citations

This map shows the geographic impact of Johan Källström's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Johan Källström with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johan Källström more than expected).

Fields of papers citing papers by Johan Källström

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Johan Källström. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Johan Källström. The network helps show where Johan Källström may publish in the future.

Co-authors

The 21 scholars most cited alongside Johan Källström, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Johan Källström Line = papers co-authored together Johan Källström links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1
A practical guide to multi-objective reinforcement learning and planning
Hit paper breakdown →
2022172
2 202219
3 202011
4 20229
5
Tunable Dynamics in Agent-Based Simulation using Multi-Objective Reinforcement Learning
20197
6 20194
7 20203
8
Reinforcement Learning for Computer Generated Forces using Open-Source Software
20193
9 20231
10 20201
11 20201

About Johan Källström

Johan Källström is a scholar working on Artificial Intelligence, Control and Systems Engineering, Management Science and Operations Research, Aerospace Engineering and Molecular Biology, having authored 11 papers that have together received 231 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Artificial Intelligence in Games (2 papers), Guidance and Control Systems (2 papers), Evolutionary Algorithms and Applications (2 papers), Simulation Techniques and Applications (2 papers), Aerospace and Aviation Technology (2 papers), Context-Aware Activity Recognition Systems (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Artificial Intelligence (83 citations), Computational Theory and Mathematics (39 citations), Industrial and Manufacturing Engineering (21 citations), Software (6 citations) and Health Informatics (2 citations). Johan Källström has collaborated with scholars based in Sweden, Belgium and Australia. Frequent co-authors include Fredrik Heintz, Diederik M. Roijers, Richard Dazeley, Conor F. Hayes, Gabriel de Oliveira Ramos, Roxana Rădulescu, Peter Vamplew, Patrick Mannion, Mathieu Reymond and Athirai A. Irissappane. Their work appears in journals such as The Aeronautical Journal, Autonomous Agents and Multi-Agent Systems, Linköping electronic conference proceedings, VUBIR (Vrije Universiteit Brussel) and Linköping studies in science and technology. Dissertations.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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