Mario Brcic

Mario Brcic
University of Zagreb · Faculty of Electrical Engineering and Computing (FER)

PhD
Making an impact using skills in Operations Research and Artificial Intelligence. Open for collaborations...reach out!

About

36
Publications
27,876
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623
Citations
Introduction
I am an assistant professor at the University of Zagreb. My research interests are stochastic combinatorial optimization and artificial general intelligence. I use approximate dynamic programming and machine learning and have an interest in interdisciplinary research. Currently, I work on combinatorial optimization augmented with machine learning, explainable artificial intelligence, AI safety, and AI ethics.

Publications

Publications (36)
Conference Paper
Full-text available
In the last decade, with availability of large datasets and more computing power, machine learning systems have achieved (super)human performance in a wide variety of tasks. Examples of this rapid development can be seen in image recognition, speech analysis, strategic game planning and many more. The problem with many state-of-the-art models is a...
Article
Parties that collaborate on projects need to synchronize their efforts. For this reason they seek a decreased rescheduling variability of the time arrangements. Proactive–reactive scheduling is important in such situations. It predominantly achieves synchronization through a shared baseline schedule and deviation penalties. As the latter currently...
Preprint
Full-text available
An impossibility theorem demonstrates that a particular problem or set of problems cannot be solved as described in the claim. Such theorems put limits on what is possible to do concerning artificial intelligence, especially the super-intelligent one. As such, these results serve as guidelines, reminders, and warnings to AI safety, AI policy, and g...
Preprint
Full-text available
The future of computation is massively parallel and heterogeneous with specialized accelerator devices and instruction sets in both edge- and cluster-computing. However, software development is bound to become the bottleneck. To extract the potential of hardware wonders, the software would have to solve the following problems: heterogeneous device...
Article
Full-text available
Anomaly detection is a hard data analysis process that requires constant creation and improvement of data analysis algorithms. Using traditional clustering algorithms to analyse data streams is impossible due to processing power and memory issues. To solve this, the traditional clustering algorithm complexity needed to be reduced, which led to the...
Article
With the increasing complexity of power system structures and the increasing penetration of renewable energy, driven primarily by the need for decarbonization, power system operation and control become challenging. Changes are resulting in an enormous increase in system complexity, wherein the number of active control points in the grid is too high...
Preprint
The data mesh is a novel data management concept that emphasises the importance of a domain before technology. The concept is still in the early stages of development and many efforts to implement and use it are expected to have negative consequences for organizations due to a lack of technological guidelines and best practices. To mitigate the ris...
Preprint
This paper deals with the mediator-wrapper architecture. It is an important architectural pattern that enables a more flexible and modular architecture in opposition to monolithic architectures for data source integration systems. This paper identifies certain realistic and concrete scenarios where the mediator-wrapper architecture underperforms. T...
Conference Paper
Full-text available
The future of computation is massively parallel and heterogeneous with specialized accelerator devices and instruction sets in both edge-and cluster-computing. However, software development is bound to become the bottleneck. To extract the potential of hardware wonders, the software would have to solve the following problems: heterogeneous device m...
Preprint
We shall have a hard look at ethics and try to extract insights in the form of abstract properties that might become tools. We want to connect ethics to games, talk about the performance of ethics, introduce curiosity into the interplay between competing and coordinating in well-performing ethics, and offer a view of possible developments that coul...
Conference Paper
Full-text available
Artificial intelligence has become mainstream and its applications will only proliferate. Specific measures must be done to integrate such systems into society for the general benefit. One of the tools for improving that is explainability which boosts trust and understanding of decisions between humans and machines. This research offers an update o...
Conference Paper
Full-text available
Scheduling is a family of combinatorial problems where we need to find optimal time arrangements for activities. Scheduling problems in applications are usually notoriously hard to solve exactly. Existing exact solving procedures, based on mathematical programming and constraint programming, usually make manually-tuned heuristic choices. These heur...
Article
Full-text available
Goods from warehouses must be scheduled in advance, prepared, routed, and delivered to shops. At least three systems directly interact within such a process: warehouse workforce scheduling, delivery scheduling, and routing system. Ideally, the whole problem with the preceding inventory management (restocking) would be solved in one optimization pas...
Preprint
Full-text available
Goods from warehouses must be scheduled in advance, prepared, routed, and delivered to shops. At least three systems directly interact within such a process: warehouse workforce scheduling, delivery scheduling, and routing system. Ideally, the whole problem with the preceding inventory management (restocking) would be solved in one optimization pas...
Preprint
Artificial intelligence (AI) has been embedded into many aspects of people's daily lives and it has become normal for people to have AI make decisions for them. Reinforcement learning (RL) models increase the space of solvable problems with respect to other machine learning paradigms. Some of the most interesting applications are in situations with...
Preprint
Full-text available
Artificial intelligence has become mainstream and its applications will only proliferate. Specific measures must be done to integrate such systems into society for the general benefit. One of the tools for improving that is explainability which boosts trust and understanding of decisions between humans and machines. This research offers an update o...
Preprint
Full-text available
Scheduling is a family of combinatorial problems where we need to find optimal time arrangements for activities. Scheduling problems in applications are usually notoriously hard to solve exactly. Existing exact solving procedures, based on mathematical programming and constraint programming, usually make manually-tuned heuristic choices. These heur...
Conference Paper
Full-text available
Last decade has seen major improvements in the performance of artificial intelligence which has driven widespread applications. Unforeseen effects of such mass-adoption has put the notion of AI safety into the public eye. AI safety is a relatively new field of research focused on techniques for building AI beneficial for humans. While there exist s...
Preprint
Full-text available
Last decade has seen major improvements in the performance of artificial intelligence which has driven widespread applications. Unforeseen effects of such mass-adoption has put the notion of AI safety into the public eye. AI safety is a relatively new field of research focused on techniques for building AI beneficial for humans. While there exist s...
Article
Full-text available
Today organizations capture and store an abundant amount of data from their interaction with clients, internal information systems, technical systems and sensors. Data captured this way comprises many useful insights that can be discovered by various analytical procedures and methods. Discovering regular and irregular data sequences in the captured...
Article
Full-text available
Proactive-reactive scheduling is important in the situations where the project collaborators need to coordinate their efforts. The coordination is mostly achieved through the combination of the shared baseline schedule and the deviation penalties. In this paper, we present an extension of predictive Gantt chart to the proactive-reactive scheduling...
Article
Full-text available
Combinatorial optimization is an area of great importance since many of the real-world problems have discrete parameters which are part of the objective function to be optimized. Development of combinatorial optimization algorithms is guided by the empirical study of the candidate ideas and their performance over a wide range of settings or scenari...
Article
Full-text available
This paper proposes an actual implementation of a well-known method [1] for spectral analysis of signals composed of harmonically related sine waves. The method itself requires computations which carried out directly according to the theoretical formulas do not yield computationally efficient implementation. Thus, utilizing matrix factorizations an...
Article
Full-text available
This paper presents a new approach to proactive reactive scheduling of stochastic resource-constrained project scheduling problems with known probability distributions of activity durations. To facilitate the search for cost-flexible proactive schedules that are adjustable and incur lower expected cost of future rescheduling, a new family of cost-b...
Conference Paper
Full-text available
Stochastic Resource Constrained Project Scheduling (SRCPS) is among the hardest combinatorial problems. Exact calculations of interesting measures, such as expected project duration and the probability of satisfying the deadline, using known probabilities are in #P even for relaxed instances of the problem where resource constraints are ignored. Th...
Conference Paper
Full-text available
Resource Constrained Project Scheduling Problems (RCPSP), especially their stochastic variants, and the methods operating on them represent a general project scheduling optimization framework. This paper presents the survey of methods and models that are put into the historical context and are categorized according to their working principles. It a...
Conference Paper
Full-text available
Software systems continuously grow in size and code complexity, the latter most evident through greater component interconnectedness. This leaves more space for bugs which introduce risks such as exposure to security threats. Combinatorial testing looks for interaction failures in order to improve the system security and effectiveness guarantees. O...
Conference Paper
Full-text available
This paper presents a proprietary application generator based on UML specification. The tool is designed for generating the source code in various programming languages from the same specification. The main characteristics of the existent tools are explained in brief. Main generator capabilities and merits are presented as well as an example of usa...
Article
Full-text available
This paper presents a application generator based on UML specification. The tool is capable of generating the source code in various programming languages from the same specification. The main characteristics of the existent tools are explained in brief. Main generator capabilities and merits are presented as well as an example of usage based on a...

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Projects (2)
Project
Using the proactive reactive scheduling for scheduling collaborative projects