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researcher

S. Lucas

43 papers hereh-index 4411.1k citations281 works total

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

author position
  • sole author2
  • first author6
  • middle author10
  • last author24

Across the 42 of 43 papers where every author was matched, so the position is known.

fields
  • cs.AI30
  • cs.NE7
  • cs.LG3
  • cs.PL1
  • cs.SE1
  • q-bio.NC1
same name
  • S. Lucas — 6 papers, h 2
  • S. Lucas — 4 papers, h 9
  • S. Lucas — 4 papers, h 4
  • S. Lucas — 2 papers, h 35
  • S. Lucas — 2 papers, h 3
  • S. Lucas — 2 papers, h 0

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
20062023
most citedTile Pattern KL-Divergence for Analysing and Evolving Game Levels

34 citations · 94 across the 29 of their papers we have counts for

collaborators
Showing 2016Show all

4 papers · 1 filter

cs.AI2016

Ms. Pac-Man Versus Ghost Team CIG 2016 Competition

Piers R. Williams, Diego Perez-Liebana, Simon M. Lucas

This paper introduces the revival of the popular Ms. Pac-Man Versus Ghost Team competition. We present an updated game engine with Partial Observability constraints, a new Multi-Ag…

cs.AI2016★ 3 cited

Rolling Horizon Coevolutionary Planning for Two-Player Video Games

Jialin Liu, Diego Pérez-Liébana, Simon M. Lucas

This paper describes a new algorithm for decision making in two-player real-time video games. As with Monte Carlo Tree Search, the algorithm can be used without heuristics and has…

cs.NE2016★ 7 cited

Optimal resampling for the noisy OneMax problem

Jialin Liu, Michael Fairbank, Diego Pérez-Liébana +1

The OneMax problem is a standard benchmark optimisation problem for a binary search space. Recent work on applying a Bandit-Based Random Mutation Hill-Climbing algorithm to the noi…

cs.AI2016★ 3 cited

Bandit-Based Random Mutation Hill-Climbing

Jialin Liu, Diego Peŕez-Liebana, Simon M. Lucas

The Random Mutation Hill-Climbing algorithm is a direct search technique mostly used in discrete domains. It repeats the process of randomly selecting a neighbour of a best-so-far…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.