Page Not Found
Page not found. Your pixels are in another canvas.
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Page not found. Your pixels are in another canvas.
About me
This is a page not in th emain menu
Published:
Water simulations
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
In this project, I aim to understand human’s needs for explainability within multi-objective decision making. This was done by reviewing currently existing methods to support the decision-makers in this field, as well as conducting interviews with the decision-makers to understand their needs. Based on the interviews, I analyze them to find common approaches used by practitioners using qualitative analysis tools.
The goal of this project is to create a suite of water mamagement-related Mo-GYM environments for training reinforcement learning agents with multipe objectives. These environments simulate problems related to managing reservoirs around the world. Currently, the number of environments for MORL available is limited and represents mostly toy-examples. With the suite of water management-related environments, it will be possible to test different MORL algorithms on real-world examples with high impact. The modular framework will also allow researchers from water management to build their simulations in an easier, unified manner
We address the challenge of explainability in MORL by focusing on interpreting the solution set to provide insights into policies with diverse trade-offs. Our aim is to assist decision-makers (DMs) in selecting and implementing solutions by developing diverse methods to help them explore the solution sets.
This project aims to develop interactive MORL approaches, where the training process is more efficient as it takes into account user’s preferences over time.
Published in Master thesis, 2020
Master thesis on different explainable techniques
Recommended citation: Osika, Z; Chlebus, M. (2020). "Comparison of tree-based models performance in prediction of marketing campaign results using Explainable Artificial Intelligence tools." Master Thesis.
Published in International Joint Conference on Artificial Intelligence, Macau 2023, 2023
Literature Review of decision support methods to explore the Pareto front in multi-objective decision making
Recommended citation: Osika, Z., Zatarain Salazar, J., Roijers, D. M., Oliehoek, F. A., & Murukannaiah, P. K. (2023). What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23 (pp. 6741–6749). International Joint Conferences on Artificial Intelligence Organization.
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.