2013/02/08 by José Hernández‐Orallo, Jose Hernandez-Orallo, Hernandez-Orallo, Jose · 1 citation
Computer Science · Economics, Econometrics and Finance · #Artificial Intelligence (cs.AI) #Cellular Automata and Applications #Complex Systems and Time Series Analysis #Computability, Logic, AI Algorithms #FOS: Computer and information sciences #cs.AI
paper · pdf · doi:10.48550/arxiv.1302.2056
arxiv created 2013/02/08 · openalex publication_date 2013/02/08 · arxiv updated 2013/02/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We analyse the complexity of environments according to the policies that need to be used to achieve high performance. The performance results for a population of policies leads to a distribution that is examined in terms of policy complexity and analysed through several diagrams and indicators. The notion of environment response curve is also introduced, by inverting the performance results into an ability scale. We apply all these concepts, diagrams and indicators to a minimalistic environment class, agent-populated elementary cellular automata, showing how the difficulty, discriminating power and ranges (previous to normalisation) may vary for several environments.