Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Aneta Neumann

View on Semantic Scholar

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Aug 2026

Insights from Multi-tasking the EAX Algorithm for the Travelling Salesperson Problem

This paper investigates integrating evolutionary multitasking with Edge Assembly Crossover (MT-EAX) to solve the classical Travelling Salesperson Problem and demonstrates that the advantage of MT-EAX derives from increased diversity through parallel search in early generations, which can be successfully preserved using...

L. Wigney, Aneta Neumann, Y. Ong et al. · 0 citations
Review Open access Jul 2026

Leveraging social media footprints for predicting college student anxiety: a machine learning approach.

BACKGROUND Anxiety is one of the most prevalent mental health concerns among college students worldwide, yet traditional assessment methods relying on self-report questionnaires are time-consuming, susceptible to response bias, and difficult to scale. Social media platforms, which students use extensively, generate ric...

Chenyan Dong, Aneta Neumann, Yingping Sun et al. · 0 citations
Book Open access Jul 2026

Hot off the Press: Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem

EDO is analyzed on a three-objective function LOTZk, which is a modification of the two-objective benchmark function (LeadingOnes, TrailingZeros), and it is proved that the GSEMO computes a set of all Pareto-optimal solutions in O(kn3) expected iterations.

D. Antipov, Aneta Neumann, Frank Neumann et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.