Jonathan Gadea Harder

ORCID: 0000-0002-0869-0865
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Machine Learning and Algorithms
  • Computability, Logic, AI Algorithms
  • Metaheuristic Optimization Algorithms Research
  • semigroups and automata theory
  • Optimization and Search Problems
  • Algorithms and Data Compression
  • Game Theory and Applications
  • Vehicle Routing Optimization Methods
  • Economic theories and models
  • Markov Chains and Monte Carlo Methods
  • Text and Document Classification Technologies
  • Advanced Optimization Algorithms Research
  • Matrix Theory and Algorithms
  • Game Theory and Voting Systems
  • Evolutionary Algorithms and Applications
  • Auction Theory and Applications
  • E-commerce and Technology Innovations

University of Potsdam
2020-2024

Hasso Plattner Institute
2021-2024

Freie Universität Berlin
2019

10.1145/3638529.3654091 article EN Proceedings of the Genetic and Evolutionary Computation Conference 2024-07-08

This paper explores the enhancement of solution diversity in evolutionary algorithms (EAs) for maximum matching problem, concentrating on complete bipartite graphs and paths. We adopt binary string encoding matchings use Hamming distance to measure diversity, aiming its maximization. Our study centers $(\mu+1)$-EA $2P-EA_D$, which are applied optimize diversity. provide a rigorous theoretical empirical analysis these algorithms. For graphs, our runtime shows that, with reasonably small...

10.48550/arxiv.2404.11784 preprint EN arXiv (Cornell University) 2024-04-17

The strategic selection of resources by selfish agents is a classical research direction, with Resource Selection Games and Congestion as prominent examples. In these games, select available their utility then depends on the number using same resources. This implies that there no distinction between agents, i.e., they are anonymous. We depart from this very general setting proposing heterogeneous strive for joint resource usage similar agents. So, instead other users given resource, our...

10.24963/ijcai.2023/301 article EN 2023-08-01

The strategic selection of resources by selfish agents is a classic research direction, with Resource Selection Games and Congestion as prominent examples. In these games, select available their utility then depends on the number using same resources. This implies that there no distinction between agents, i.e., they are anonymous. We depart from this very general setting proposing heterogeneous strive for joint resource usage similar agents. So, instead other users given resource, our model...

10.48550/arxiv.2305.00843 preprint EN other-oa arXiv (Cornell University) 2023-01-01

While most theoretical run time analyses of discrete randomized search heuristics focused on finite spaces, we consider the space $\mathbb{Z}^n$. This is a further generalization multi-valued decision variables $\{0,\ldots,r-1\}^n$. We as fitness functions distance to (unique) non-zero optimum $a$ (based $L_1$-metric) and \ooea which mutates by applying step-operator each component that determined be varied. For changing $\pm 1$, show expected optimization $\Theta(n \cdot (|a|_{\infty} +...

10.48550/arxiv.2307.11855 preprint EN cc-by arXiv (Cornell University) 2023-01-01

Let S be a set of points located in the unit square [0, 1]², which contains (0, 0). An open conjecture states that for any it is possible to cover half area by rectangles inside square, with conditions lower-left corner each rectangle point and are non-overlapping axes-parallel. The focus this thesis suggest an algorithm, determines what maximum can covered rectangles. This algorithm improves running time currently best-known poly(n)*n! poly(n)*2^n use dynamic programming. To analyze how...

10.2139/ssrn.3463959 article EN SSRN Electronic Journal 2019-01-01

We study learning of indexed families from positive data where a learner can freely choose hypothesis space (with uniformly decidable membership) comprising at least the languages to be learned. This abstracts very universal task which found in many areas, for example (subsets of) regular or natural languages. are interested various restrictions on learning, such as consistency, conservativeness set-drivenness, exemplifying restrictions. Building previous results literature, we provide...

10.48550/arxiv.2010.09460 preprint EN other-oa arXiv (Cornell University) 2020-01-01

In language learning in the limit, most common type of hypothesis is to give an enumerator for a language. This so-called $W$-index allows naming arbitrary computably enumerable languages, with drawback that even membership problem undecidable. this paper we use different system which decidable namely programs characteristic functions (called $C$-indices). These indices have it now not whether given legal $C$-index. first analysis $C$-indices, structured account power various restrictions...

10.48550/arxiv.2011.09866 preprint EN other-oa arXiv (Cornell University) 2020-01-01
Coming Soon ...