Johan Källström

According to our database, Johan Källström authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning.

Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers

CoRR, 2024

2023

Reinforcement Learning for Improved Utility of Simulation-Based Training.

Johan Källström

PhD thesis, 2023

Model-Based Actor-Critic for Multi-Objective Reinforcement Learning with Dynamic Utility Functions.

Johan Källström, Fredrik Heintz

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

A Brief Guide to Multi-Objective Reinforcement Learning and Planning.

Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Scalar Reward is Not Enough.

Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Friedrik Hentz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021).

Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale

Auton. Agents Multi Agent Syst., 2022

A practical guide to multi-objective reinforcement learning and planning.

Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Auton. Agents Multi Agent Syst., 2022

2020

Agent Coordination in Air Combat Simulation using Multi-Agent Deep Reinforcement Learning.

Johan Källström, Fredrik Heintz

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Improving Usability of Search and Rescue Decision Support Systems: WARA-PS Case Study.

Veronika Domova, Erik Gärtner, Fredrik Präntare, Martin Pallin, Johan Källström, Nikita Korzhitskii

Proceedings of the 25th IEEE International Conference on Emerging Technologies and Factory Automation, 2020

Adaptive Agent-Based Simulation for Individualized Training.

Johan Källström

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020