Bounded Languages Meet Cellular Automata with Sparse Communication

Cellular automata are one-dimensional arrays of interconnected interacting finite automata. We investigate one of the weakest classes, the real-time one-way cellular automata, and impose an additional restriction on their inter-cell communication by bounding the number of allowed uses of the links between cells. Moreover, we consider the devices as acceptors for bounded languages in order to explore the borderline at which non-trivial decidability problems of cellular automata classes become decidable. It is shown that even devices with drastically reduced communication, that is, each two neighboring cells may communicate only constantly often, accept bounded languages that are not semilinear. If the number of communications is at least logarithmic in the length of the input, several problems are undecidable. The same result is obtained for classes where the total number of communications during a computation is linearly bounded

Finite Automata for the Sub- and Superword Closure of CFLs: Descriptional and Computational Complexity

We answer two open questions by (Gruber, Holzer, Kutrib, 2009) on the state-complexity of representing sub- or superword closures of context-free grammars (CFGs): (1) We prove a (tight) upper bound of $2^{\mathcal{O}(n)}$ on the size of nondeterministic finite automata (NFAs) representing the subword closure of a CFG of size $n$. (2) We present a family of CFGs for which the minimal deterministic finite automata representing their subword closure matches the upper-bound of $2^{2^{\mathcal{O}(n)}}$ following from (1). Furthermore, we prove that the inequivalence problem for NFAs representing sub- or superword-closed languages is only NP-complete as opposed to PSPACE-complete for general NFAs. Finally, we extend our results into an approximation method to attack inequivalence problems for CFGs

Transductions Computed by One-Dimensional Cellular Automata

Cellular automata are investigated towards their ability to compute transductions, that is, to transform inputs into outputs. The families of transductions computed are classified with regard to the time allowed to process the input and to compute the output. Since there is a particular interest in fast transductions, we mainly focus on the time complexities real time and linear time. We first investigate the computational capabilities of cellular automaton transducers by comparing them to iterative array transducers, that is, we compare parallel input/output mode to sequential input/output mode of massively parallel machines. By direct simulations, it turns out that the parallel mode is not weaker than the sequential one. Moreover, with regard to certain time complexities cellular automaton transducers are even more powerful than iterative arrays. In the second part of the paper, the model in question is compared with the sequential devices single-valued finite state transducers and deterministic pushdown transducers. It turns out that both models can be simulated by cellular automaton transducers faster than by iterative array transducers.Comment: In Proceedings AUTOMATA&JAC 2012, arXiv:1208.249

Measuring Communication in Parallel Communicating Finite Automata

Systems of deterministic finite automata communicating by sending their states upon request are investigated, when the amount of communication is restricted. The computational power and decidability properties are studied for the case of returning centralized systems, when the number of necessary communications during the computations of the system is bounded by a function depending on the length of the input. It is proved that an infinite hierarchy of language families exists, depending on the number of messages sent during their most economical recognitions. Moreover, several properties are shown to be not semi-decidable for the systems under consideration.Comment: In Proceedings AFL 2014, arXiv:1405.527

Counter Machines and Distributed Automata: A Story about Exchanging Space and Time

We prove the equivalence of two classes of counter machines and one class of distributed automata. Our counter machines operate on finite words, which they read from left to right while incrementing or decrementing a fixed number of counters. The two classes differ in the extra features they offer: one allows to copy counter values, whereas the other allows to compute copyless sums of counters. Our distributed automata, on the other hand, operate on directed path graphs that represent words. All nodes of a path synchronously execute the same finite-state machine, whose state diagram must be acyclic except for self-loops, and each node receives as input the state of its direct predecessor. These devices form a subclass of linear-time one-way cellular automata.Comment: 15 pages (+ 13 pages of appendices), 5 figures; To appear in the proceedings of AUTOMATA 2018

Agentes inteligentes: modelos formales y aplicaciones para la educación

En este trabajo se presenta el proyecto de investigación Agentes Inteligentes. Modelos Formales y Aplicaciones para la Educación. El proyecto tiene como objetivo general el estudio y desarrollo de técnicas de Inteligencia Artificial para dotar de inteligencia, conocimiento y capacidades cognitivas a agentes inmersos en ambientes complejos. Asimismo, el proyecto se abocará al estudio de modelos formales buscando identificar posibles aplicaciones en el contexto educativo. En este sentido, se procurará desarrollar modelos y categorías que contribuyan a la producción del marco teórico que se ocupa de estudiar la inclusión de la computación en la educación, asumiendo este campo de conocimiento como disciplina teórica en construcción. En el proyecto convergen diferentes líneas de investigación en el contexto de los Agentes Inteligentes, que articuladas describen el objeto de estudio y definen las actividades de investigación: modelos formales e identificación de posibles aplicaciones al campo educativo.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informática (RedUNCI

Agentes inteligentes: modelos formales y aplicaciones para la educación

En este trabajo se presenta el proyecto de investigación Agentes Inteligentes. Modelos Formales y Aplicaciones para la Educación. El proyecto tiene como objetivo general el estudio y desarrollo de técnicas de Inteligencia Artificial para dotar de inteligencia, conocimiento y capacidades cognitivas a agentes inmersos en ambientes complejos. Asimismo, el proyecto se abocará al estudio de modelos formales buscando identificar posibles aplicaciones en el contexto educativo. En este sentido, se procurará desarrollar modelos y categorías que contribuyan a la producción del marco teórico que se ocupa de estudiar la inclusión de la computación en la educación, asumiendo este campo de conocimiento como disciplina teórica en construcción. En el proyecto convergen diferentes líneas de investigación en el contexto de los Agentes Inteligentes, que articuladas describen el objeto de estudio y definen las actividades de investigación: modelos formales e identificación de posibles aplicaciones al campo educativo.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informática (RedUNCI