Over the years many brave gamers have whole-heartedly taken up the challenge to restore a mixed Rubik's cube to it's colorful and perfect original configuration, only to find the solution lingering just out of their grasp time and time again. The world's most famous puzzle, simultaneously beloved and despised for it's beautiful simple complexity, the Rubiks Cube has been frustrating gamers since Erno Rubik invented it back in 1974. According to the obtained results, we have verified the feasibility of using GP in this domain, and the enhancement in the search efficiency and interpretability of solutions due to the Tarpeian method.How to Solve the Rubik's Cube in Seven Steps
Besides, in order to improve the solution size and the computational time, we use the Tarpeian method which controls the bloat effect of GP.
In this paper, the missing values problem benefits from the definition of if-unknown, a new operation which is more appropriate to the domain data semantics. We take advantages of GP flexibility, particularly, the possibility of defining new operations. GP evolves an expression, equivalent to a binary classifier, which predicts if a given pair of proteins. Genetic Programming (GP) is applied to this domain. Proceeding of: 11th Ibero-American Conference on AI (IBERAMIA 2008), Lisbon, Portugal, 14-17 Octubre 2008 One of the definitely unsolved main problems in molecular biology is the protein-protein functional association prediction problem.
In a first set of runs, we demonstrate that StarCraftGP ultimately generates a competitive strategy for a Zerg bot, able to defeat several human-designed bots. The proposed approach generates strategies as C++ classes, that are then compiled and executed inside the OpprimoBot open-source framework. In this paper, we present the preliminary results of StarCratfGP, a framework able to evolve a complete strategy for StarCraft, from the building plan, to the composition of squads, up to the set of rules that define the bot's behavior during the game. In literature, various works exploit evolutionary computation to optimize particular aspects of the game, from squad formation to map exploration but so far, no evolutionary approach has been applied to the development of a complete strategy from scratch. trees, large number of units with unique features, and potential for optimization both at the strategical and tactical level. Several characteristics make this game particularly appealing for researchers, such as: asymmetric balanced factions, considerable complexity of the technology. Many research lines aimed at developing Artificial Intelligences, or " bots ", capable of challenging human players, use StarCraft as a platform. Among Real-Time Strategy games few titles have enjoyed the continued success of StarCraft.
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