Decision-Theoretic Planning with Person Trajectory Prediction for Social Navigation

Robots navigating in a social way should reason about people intentions when acting. For instance, in applications like robot guidance or meeting with a person, the robot has to consider the goals of the people. Intentions are inherently nonobservable, and thus we propose Partially Observable Markov Decision Processes (POMDPs) as a decision-making tool for these applications. One of the issues with POMDPs is that the prediction models are usually handcrafted. In this paper, we use machine learning techniques to build prediction models from observations. A novel technique is employed to discover points of interest (goals) in the environment, and a variant of Growing Hidden Markov Models (GHMMs) is used to learn the transition probabilities of the POMDP. The approach is applied to an autonomous telepresence robot

Simbología de poder en Guayabo de Turrialba

Inferences are made on the symbolic purpose of the architectonic compounds at the Guayabo de Turrialba National Monument, in regard to rank and sociopolitical power in the prehispanic chiefdom society of the Reventazón watershed (200 B.C.-A.D. 1300). Data analyses are performed on the cultural history, chronology of monumental architecture, size and volume of public works, and estimated requirements of labor and building materials. Se examina el propósito simbólico de los conjuntos arquitectónicos del Monumento Nacional Guayabo de Turrialba, respecto del fenómeno de rango y poder sociopolítico en la antigua sociedad cacical de la cuenca media del Reventazón (200 a.C.-1300 d.C.). Se evalúa la historia cultural; cronología y estructura arquitectónica; volumen de las obras civiles y requerimientos de materiales constructivos y de fuerza de trabajo. 

New applications for an old tool

First, the dependency graph technique, not so far from its current application, was developed trying to nd the shortest computations for membrane systems solving instances of SAT. Certain families of membrane systems have been demonstrated to be non-effcient by means of the reduction of nding an accepting computation (respectively, rejecting computation) to the problem of reaching from a node of the dependency graph to another one. In this paper, a novel application to this technique is explained. Supposing that a problem can be solved by means of a kind of membrane systems leads to a contradiction by means of using the dependency graph as a reasoning method. In this case, it is demonstrated that a single system without dissolution, polarizations and cooperation cannot distinguish a single object from more than one object. An extended version of this work will be presented in the 20th International Conference on Membrane Computing.Ministerio de Industria, Economía y Competitividad TIN2017-89842-

Dependency Graph Technique Revisited

The dependency graph technique was initially thought as a method to find short paths in the computation tree of a membrane system using weak metrics. It could be used to obtain reasonably fast SAT-solvers, capable of competing with the ones available in the literature. Later on, they were used as a method to demonstrate the non-efficiency of some membrane systems, capturing the dynamics of the systems by a static directed graph structure. Recently, the dependency graphs have also been used to establish negative results in Membrane Computing. Specifically, in this work, demonstrating the inability of a kind of membrane system to solve some decision problems efficiently by means of a single system.Ministerio de Economía, Industria y Competitividad TIN2017-89842-

MeCoSim: A general purpose software tool for simulating biological phenomena by means of P Systems

In recent years, the increasing importance of the computational systems biology is leading to an impressive growth of the knowledge of several real-life phenomena. In this framework, membrane computing is an emergent branch within natural computing that has been succesfully used to model biological phenomena. The study of these phenomena usually requires the execution of virtual experiments using mechanisms of simulation, implying the development of ad-hoc tools to simulate. However, the advance of the research is demanding general solutions to avoid the necessity of custom software developments for each matter of study, when there are some common problems to resolve. MeCoSim (Membrane Computing Simulator) is a first step in this direction providing the users a customizable application to generate custom simulators based on membrane computing by simply writing a configuration file.Ministerio de Educación y Ciencia TIN2009–13192Junta de Andalucía P08–TIC-0420

A P–Lingua Based Simulator for Spiking Neural P Systems

The research within the field of Spiking Neural P systems (SN P systems, for short) is focusing mainly in the study of the computational completeness (they are equivalent in power to Turing machines) and computational efficiency of this kind of systems. These devices have been shown capable of providing polynomial time solutions to computationally hard problems by making use of an exponential workspace constructed in a natural way. In order to experimentally explore this computational power, it is necessary to develop software that provides simulation tools (simulators) for the existing variety of SN P systems. Such simulators allow us to carry out computations of solutions to NP-complete problems on certain instances. Within this trend, P-Lingua provides a standard language for the definition of P systems. As part of the same project, pLinguaCore library provides particular implementations of parsers and simulators for the models specified in P-Lingua. In this paper, an extension of the P-Lingua language to define SN P systems is presented, along with an upgrade of pLinguaCore including a parser and a new simulator for the variants of these systems included in the language.Ministerio de Ciencia e Innovación TIN2009–13192Junta de Andalucía P08-TIC-0420

From NP-Completeness to DP-Completeness: A Membrane Computing Perspective

Presumably efficient computing models are characterized by their capability to provide polynomial-time solutions for NPcomplete problems. Given a classRof recognizer membrane systems,Rdenotes the set of decision problems solvable by families from R in polynomial time and in a uniform way. PMCR is closed under complement and under polynomial-time reduction. +erefore, if R is a presumably efficient computing model of recognizer membrane systems, then NP ∪ co-NP ⊆PMCR. In this paper, the lower bound NP ∪ co-NP for the time complexity class PMCR is improved for any presumably efficient computing model R of recognizer membrane systems verifying some simple requirements. Specifically, it is shown that DP ∪ co-DP is a lower bound for such PMCR, where DP is the class of differences of any two languages in NP. Since NP ∪ co-NP⊆DP ∩ co- DP, this lower bound for PMCR delimits a thinner frontier than that with NP ∪ co-NP.Ministerio de Economía, Industria y Competitividad TIN2017-89842-

A new P-Lingua toolkit for agile development in membrane computing

Membrane computing is a massively parallel and non-deterministic bioinspired computing paradigm whose models are called P systems. Validating and testing such models is a challenge which is being overcome by developing simulators. Regardless of their heterogeneity, such simulators require to read and interpret the models to be simulated. To this end, P-Lingua is a high-level P system definition language which has been widely used in the last decade. The P-Lingua ecosystem includes not only the language, but also libraries and software tools for parsing and simulating membrane computing models. Each version of P-Lingua supported new types or variants of P systems. This leads to a shortcoming: Only a predefined list of variants can be used, thus making it difficult for researchers to study custom ones. Moreover, derivation modes cannot be user-defined, i.e, the way in which P system computations should be generated is determined by the simulation algorithm in the source code. The main contribution of this paper is a completely new design of the P-Lingua language, called P-Lingua 5, in which the user can define custom variants and derivation modes, among other improvements such as including procedural programming and simulation directives. It is worth mentioning that it has backward-compatibility with previous versions of the language. A completely new set of command-line tools is provided for parsing and simulating P-Lingua 5 files. Finally, several examples are included in this paper covering the most common P system types.Agencia Estatal de Investigación TIN2017-89842-

Design of Specific P Systems Simulators on GPUs

In order to validate P system models and to assist on their formal verification, simulators are indispensable. Moreover, having effi-cient simulation tools is crucial, and for this purpose, parallel platforms should be employed. So far, several parallel simulators for P systems have been developed, specifically targeting GPUs (Graphics Processing Units). Although being a hot topic within Membrane Computing, map-ping P system parallelism on GPUs is still not a mature area. In the past, we have successfully accelerated the simulation of two specific fam-ilies of P systems solving SAT with GPUs, and learned in the process some semantics ingredients that fit well on these parallel devices. We are extending this exploration by designing an specific simulator of a P system model for the FACTORIZATION problem. In this paper, we analyse the two main approaches for simulators, and depict some design decisions required for this case study.Ministerio de Industria, Economía y Competitividad TIN2017-89842-

Dendrite P Systems Toolbox: Representation, Algorithms and Simulators

Dendrite P systems (DeP systems) are a recently introduced neural-like model of computation. They provide an alternative to the more classical spiking neural (SN) P systems. In this paper, we present the first software simulator for DeP systems, and we investigate the key features of the representation of the syntax and semantics of such systems. First, the conceptual design of a simulation algorithm is discussed. This is helpful in order to shade a light on the differences with simulators for SN P systems, and also to identify potential parallelizable parts. Second, a novel simulator implemented within the PLingua simulation framework is presented. Moreover, MeCoSim, a GUI tool for abstract representation of problems based on P system models has been extended to support this model. An experimental validation of this simulator is also covered.Ministerio de Economía, Industria y Competitividad TIN2017-89842-P (MABICAP