English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The diversity of agent behaviors is an important topic for the quality ofvideo games and virtual environments in general. Offering the most compellingexperience for users with different skills is a difficult task, and usuallyneeds important manual human effort for tuning existing code. This can get evenharder when dealing with adaptive difficulty systems. Our paper's main purposeis to create a framework that can automatically create behaviors for gameagents of different difficulty classes and enough diversity. In parallel withthis, a second purpose is to create more automated tests for showing defects inthe source code or possible logic exploits with less human effort.

Automatic difficulty management and testing in games using a framework based on behavior trees and genetic algorithms