The Computational Power of Benenson Automata

The development of autonomous molecular computers capable of making independent decisions in vivo regarding local drug administration may revolutionize medical science. Recently Benenson at el (2004) have envisioned one form such a ``smart drug'' may take by implementing an in vitro scheme, in which a long DNA state molecule is cut repeatedly by a restriction enzyme in a manner dependent upon the presence of particular short DNA ``rule molecules.'' To analyze the potential of their scheme in terms of the kinds of computations it can perform, we study an abstraction assuming that a certain class of restriction enzymes is available and reactions occur without error. We also discuss how our molecular algorithms could perform with known restriction enzymes. By exhibiting a way to simulate arbitrary circuits, we show that these ``Benenson automata'' are capable of computing arbitrary Boolean functions. Further, we show that they are able to compute efficiently exactly those functions computable by log-depth circuits. Computationally, we formalize a new variant of limited width branching programs with a molecular implementation.Comment: 18 page

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Can geocomputation save urban simulation? Throw some agents into the mixture, simmer and wait ...

There are indications that the current generation of simulation models in practical, operational uses has reached the limits of its usefulness under existing specifications. The relative stasis in operational urban modeling contrasts with simulation efforts in other disciplines, where techniques, theories, and ideas drawn from computation and complexity studies are revitalizing the ways in which we conceptualize, understand, and model real-world phenomena. Many of these concepts and methodologies are applicable to operational urban systems simulation. Indeed, in many cases, ideas from computation and complexity studies—often clustered under the collective term of geocomputation, as they apply to geography—are ideally suited to the simulation of urban dynamics. However, there exist several obstructions to their successful use in operational urban geographic simulation, particularly as regards the capacity of these methodologies to handle top-down dynamics in urban systems. This paper presents a framework for developing a hybrid model for urban geographic simulation and discusses some of the imposing barriers against innovation in this field. The framework infuses approaches derived from geocomputation and complexity with standard techniques that have been tried and tested in operational land-use and transport simulation. Macro-scale dynamics that operate from the topdown are handled by traditional land-use and transport models, while micro-scale dynamics that work from the bottom-up are delegated to agent-based models and cellular automata. The two methodologies are fused in a modular fashion using a system of feedback mechanisms. As a proof-of-concept exercise, a micro-model of residential location has been developed with a view to hybridization. The model mixes cellular automata and multi-agent approaches and is formulated so as to interface with meso-models at a higher scale

Key challenges in agent-based modelling for geo-spatial simulation

Agent-based modelling (ABM) is fast becoming the dominant paradigm in social simulation due primarily to a worldview that suggests that complex systems emerge from the bottom-up, are highly decentralised, and are composed of a multitude of heterogeneous objects called agents. These agents act with some purpose and their interaction, usually through time and space, generates emergent order, often at higher levels than those at which such agents operate. ABM however raises as many challenges as it seeks to resolve. It is the purpose of this paper to catalogue these challenges and to illustrate them using three somewhat different agent-based models applied to city systems. The seven challenges we pose involve: the purpose for which the model is built, the extent to which the model is rooted in independent theory, the extent to which the model can be replicated, the ways the model might be verified, calibrated and validated, the way model dynamics are represented in terms of agent interactions, the extent to which the model is operational, and the way the model can be communicated and shared with others. Once catalogued, we then illustrate these challenges with a pedestrian model for emergency evacuation in central London, a hypothetical model of residential segregation tuned to London data which elaborates the standard Schelling (1971) model, and an agent-based residential location built according to spatial interactions principles, calibrated to trip data for Greater London. The ambiguities posed by this new style of modelling are drawn out as conclusions

The Repast Simulation/Modelling System for Geospatial Simulation

The use of simulation/modelling systems can simplify the implementation of agent-based models. Repast is one of the few simulation/modelling software systems that supports the integration of geospatial data especially that of vector-based geometries. This paper provides details about Repast specifically an overview, including its different development languages available to develop agent-based models. Before describing Repast’s core functionality and how models can be developed within it, specific emphasis will be placed on its ability to represent dynamics and incorporate geographical information. Once these elements of the system have been covered, a diverse list of Agent-Based Modelling (ABM) applications using Repast will be presented with particular emphasis on spatial applications utilizing Repast, in particular, those that utilize geospatial data

Urban Atlas, land use modelling and spatial metric techniques

Recently, through the GMES program of ESA the Urban Atlas dataset was released. The Urban Atlas is providing pan-European comparable land use and land cover data for Large Urban Zones with more than 100.000 inhabitants as defined by the Urban Audit. The production of the various datasets started in 2009 and is expected to be completed by the end of 2011. At presently datasets for more than 150 urban areas have been released. Most importantly the datasets can be freely downloaded and distributed. The availability of such a huge dataset produced with the same standards will have a major impact on the development of urban transportation models and the comparative analysis of the urban areas across Europe. Combined with the data sets that will be developed from the various Census of population it could become the basis for the application of various models in the next ten years. In this paper two major themes are discussed. First, how the current state of art in urban modeling (behavioral, cellular automata and statistical) can use these models, what type of additional data might be needed and how these datasets can be combined with other data for developing land use transportation models. Second, spatial metric techniques are used to define indicators for the landscape that could be used for comparing the structure and the form of the various cities. In the last ten years there has been an increasing interest in applying spatial metric techniques analysis of urban environments, to examine unique spatial components of intra-and inter-city urban structure, as well as, the dynamics of change. The landscape perspective assumes abrupt transitions between individual patches that result in distinct edges. These measures provide a link between the detailed spatial structures that result from urban change processes. The spatial metric indicators were developed for several cities and are then used for a comparative study of city typologies and urban fabric characteristics.

Computational genes: a tool for molecular diagnosis and therapy of aberrant mutational phenotype

<p>Abstract</p> <p>Background</p> <p>A finite state machine manipulating information-carrying DNA strands can be used to perform autonomous molecular-scale computations at the cellular level.</p> <p>Results</p> <p>We propose a new finite state machine able to detect and correct aberrant molecular phenotype given by mutated genetic transcripts. The aberrant mutations trigger a cascade reaction: specific molecular markers as input are released and induce a spontaneous self-assembly of a wild type protein or peptide, while the mutational disease phenotype is silenced. We experimentally demostrated in <it>in vitro </it>translation system that a viable protein can be autonomously assembled.</p> <p>Conclusion</p> <p>Our work demostrates the basic principles of computational genes and particularly, their potential to detect mutations, and as a response thereafter administer an output that suppresses the aberrant disease phenotype and/or restores the lost physiological function.</p