Tabla de Contenidos: “…Object Database PitfallsTangram; Tangram CRUD: create, read, update, delete; Database Abstraction; Trivial Mapping; Class::DBI; Relationships; Class::DBI extensions; Other Contenders; Practical Uses in Web Applications; Class::DBI and the Template Toolkit; Maypole; Other Application Frameworks; Conclusion; Natural Language Tools; Perl and Natural Languages; Handling English Text; Pluralizations and Inflections; Converting Words to Numbers; Modules for Parsing English; Splitting Up Text; Stemming and Stopwording; Categorization and Extraction; Bayesian Analysis; Keyword Extraction and Summary…”

Tabla de Contenidos: “…PERÍMETRO Y SUPERFICIE DE LAS FIGURASACTIVIDADES CON EL TANGRAM; 1. CONSTRUIMOS TANGRAMS; 2. COMPARAMOS FIGURAS; 3. …”

Tabla de Contenidos: “…Negative/Positive Cube Illusion -- 5.3. Tangrams -- 5.4. Inside-out Cube Puzzle -- 5.5. Left-to-right Transformation Illusion -- 5.6. …”

Sumario

Tabla de Contenidos: “…4.1 Generating Attractor Caches from Sub-Games -- 4.2 Constructing Sub-games from Abstract Strategy Templates -- 5 Game Solving with Abstract Template-Based Caching -- 6 Experimental Evaluation -- 7 Related Work -- 8 Conclusion -- References -- Learning -- Bisimulation Learning -- 1 Introduction -- 2 Illustrative Example -- 3 Stutter-Insensitive Bisimulations of Deterministic Transition Systems -- 3.1 Model Checking -- 4 Counterexample-Guided Bisimulation Learning -- 4.1 Learner-Verifier Framework for Bisimulation Learning -- 4.2 Binary Decision Tree Partition Templates -- 5 Experimental Evaluation -- 5.1 Discrete-Time Clock Synchronization -- 5.2 Conditional Termination -- 6 Conclusion -- References -- Regular Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Regular Languages -- 3.2 Rational Transductions -- 3.3 Markov Decision Processes -- 4 Regular Markov Decision Processes -- 4.1 Undecidability of Values -- 4.2 Discounted Optimization -- 4.3 Finiteness Conditions -- 4.4 Q-Learning in RMDPs -- 5 Deep Regular Reinforcement Learning -- 5.1 Token Passing -- 5.2 Duplicating Pebbles -- 5.3 Shunting Yard Algorithm -- 5.4 Modified Tangrams -- 6 Conclusion -- References -- LTL Learning on GPUs -- 1 Introduction -- 2 Formal Preliminaries -- 3 High-Level Structure of the Algorithm -- 4 In-Memory Representation of Search Space -- 5 Correctness and Complexity of the Branch-Free Implementation of Temporal Operators -- 6 Relaxed Uniqueness Checks -- 7 Divide &amp -- Conquer -- 8 Evaluation of Algorithm Performance -- 9 Conclusion -- References -- Safe Exploration in Reinforcement Learning by Reachability Analysis over Learned Models -- 1 Introduction -- 2 Problem Setup -- 3 Verified Exploration Through Learned Models -- 3.1 Symbolic Environment Models -- 3.2 Shielding for Verified Safe Exploration…”