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researcher

A. Khalifa

48 papers hereh-index 262.4k citations74 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author9
  • middle author37
  • last author1

Across the 47 of 48 papers where every author was matched, so the position is known.

fields
  • cs.AI26
  • cs.LG12
  • cs.NE6
  • cs.HC2
  • cs.CL1
  • cs.IR1
same name
  • A. Khalifa — 2 papers, h 8
  • A. Khalifa — 1 paper, h 7
  • A. Khalifa — 1 paper, h 16
  • A. Khalifa — 1 paper, h 2
  • A. Khalifa — 1 paper, h 6
  • A. Khalifa — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedDeep Learning for Procedural Content Generation

143 citations · 546 across the 35 of their papers we have counts for

collaborators
Showing 2022 · cs.AIShow all

4 papers · 2 filters

cs.AI2022★ 25 cited

Generative Personas That Behave and Experience Like Humans

Matthew Barthet, Ahmed Khalifa, Antonios Liapis +1

Using artificial intelligence (AI) to automatically test a game remains a critical challenge for the development of richer and more complex game worlds and for the advancement of A…

cs.AI2022

Mutation Models: Learning to Generate Levels by Imitating Evolution

Ahmed Khalifa, Michael Cerny Green, Julian Togelius

Search-based procedural content generation (PCG) is a well-known method for level generation in games. Its key advantage is that it is generic and able to satisfy functional constr…

cs.AI2022★ 1 cited

Persona-driven Dominant/Submissive Map (PDSM) Generation for Tutorials

Michael Cerny Green, Ahmed Khalifa, M Charity +1

In this paper, we present a method for automated persona-driven video game tutorial level generation. Tutorial levels are scenarios in which the player can explore and discover dif…

cs.AI2022

Predicting Personas Using Mechanic Frequencies and Game State Traces

Michael Cerny Green, Ahmed Khalifa, M Charity +2

We investigate how to efficiently predict play personas based on playtraces. Play personas can be computed by calculating the action agreement ratio between a player and a generati…

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