How Turing parasites expand the computational landscape of digital life

Why are living systems complex? Why does the biosphere contain living beings with complexity features beyond those of the simplest replicators? What kind of evolutionary pressures result in more complex life forms? These are key questions that pervade the problem of how complexity arises in evolution. One particular way of tackling this is grounded in an algorithmic description of life: living organisms can be seen as systems that extract and process information from their surroundings in order to reduce uncertainty. Here we take this computational approach using a simple bit string model of coevolving agents and their parasites. While agents try to predict their worlds, parasites do the same with their hosts. The result of this process is that, in order to escape their parasites, the host agents expand their computational complexity despite the cost of maintaining it. This, in turn, is followed by increasingly complex parasitic counterparts. Such arms races display several qualitative phases, from monotonous to punctuated evolution or even ecological collapse. Our minimal model illustrates the relevance of parasites in providing an active mechanism for expanding living complexity beyond simple replicators, suggesting that parasitic agents are likely to be a major evolutionary driver for biological complexity.Comment: 13 pages, 8 main figures, 1 appendix with 5 extra figure

Effects of Anticipation in Individually Motivated Behaviour on Control and Survival in a Multi-Agent Scenario with Resource Constraints

This is an open access article distributed under the Creative Commons Attribution License CC BY 3.0 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Self-organization and survival are inextricably bound to an agent’s ability to control and anticipate its environment. Here we assess both skills when multiple agents compete for a scarce resource. Drawing on insights from psychology, microsociology and control theory, we examine how different assumptions about the behaviour of an agent’s peers in the anticipation process affect subjective control and survival strategies. To quantify control and drive behaviour, we use the recently developed information-theoretic quantity of empowerment with the principle of empowerment maximization. In two experiments involving extensive simulations, we show that agents develop risk-seeking, risk-averse and mixed strategies, which correspond to greedy, parsimonious and mixed behaviour. Although the principle of empowerment maximization is highly generic, the emerging strategies are consistent with what one would expect from rational individuals with dedicated utility models. Our results support empowerment maximization as a universal drive for guided self-organization in collective agent systemsPeer reviewedFinal Published versio

The discrete dynamics of small-scale spatial events: agent-based models of mobility in carnivals and street parades

Small-scale spatial events are situations in which elements or objects vary in such away that temporal dynamics is intrinsic to their representation and explanation. Someof the clearest examples involve local movement from conventional traffic modelingto disaster evacuation where congestion, crowding, panic, and related safety issue arekey features of such events. We propose that such events can be simulated using newvariants of pedestrian model, which embody ideas about how behavior emerges fromthe accumulated interactions between small-scale objects. We present a model inwhich the event space is first explored by agents using ?swarm intelligence?. Armedwith information about the space, agents then move in an unobstructed fashion to theevent. Congestion and problems over safety are then resolved through introducingcontrols in an iterative fashion and rerunning the model until a ?safe solution? isreached. The model has been developed to simulate the effect of changing the route ofthe Notting Hill Carnival, an annual event held in west central London over 2 days inAugust each year. One of the key issues in using such simulation is how the processof modeling interacts with those who manage and control the event. As such, thischanges the nature of the modeling problem from one where control and optimizationis external to the model to one where this is intrinsic to the simulation

Teaching agents to learn: from user study to implementation

Graphical user interfaces have helped center computer use on viewing and editing, rather than on programming. Yet the need for end-user programming continues to grow. Software developers have responded to the demand with a barrage of customizable applications and operating systems. But the learning curve associated with a high level of customizability-even in GUI-based operating systems-often prevents users from easily modifying their software. Ironically, the question has become, "What is the easiest way for end users to program?" Perhaps the best way to customize a program, given current interface and software design, is for users to annotate tasks-verbally or via the keyboard-as they are executing them. Experiments have shown that users can "teach" a computer most easily by demonstrating a desired behavior. But the teaching approach raises new questions about how the system, as a learning machine, will correlate, generalize, and disambiguate a user's instructions. To understand how best to create a system that can learn, the authors conducted an experiment in which users attempt to train an intelligent agent to edit a bibliography. Armed with the results of these experiments, the authors implemented an interactive machine learning system, which they call Configurable Instructible Machine Architecture. Designed to acquire behavior concepts from few examples, Cima keeps users informed and allows them to influence the course of learning. Programming by demonstration reduces boring, repetitive work. Perhaps the most important lesson the authors learned is the value of involving users in the design process. By testing and critiquing their design ideas, users keep the designers focused on their objective: agents that make computer-based work more productive and more enjoyable

Joint modeling of arrivals and parking durations for freight loading zones: Potential applications to improving urban logistics

This paper analyzes truck parking patterns in urban freight loading zones by jointly modeling the vehicle arrival rates and the parking durations. Three models were explored: 1) Count data (Negative Binomial) for vehicle arrivals, 2) Survival (Weibull) model for parking duration and 3) A joint model for arrivals and duration. The count data model estimates the parking demand i.e., the rate of truck arrival, while the survival model estimates the probability that a truck is parked for one more minute. The joint model is compared with separate models for predictability and performance. The dataset used in this research is obtained using a mobile phone parking application, at eight loading zones in the city Vic, Spain over an 18-month period from July 2018 to December 2019, comprised of vehicle parking durations, date, time of arrival and departure, professional activity, and vehicle type (weight). The parking activity data are complemented with built in environment variables of the loading zones, such as the number of establishments in a certain radius, the average walking distance to establishments, the presence of pedestrian pavement, the number of traffic lanes, among others. The joint model outperforms the models estimating the arrival rates and durations separately in goodness of fit and predictability. The model results showed that truck arrival rates vary significantly across days of the week, months, and arrival times. The parking durations are highly dependent on professional activity, vehicle type, and size. Tuesdays and Wednesdays have higher arrival rates compared to other days of a week (except Sundays). Among activities, the transport and parcels require longer parking durations. Among the vehicle types, trucks with gross weight larger than 3.5 tons park longer. This paper concludes by explaining the potential of these modeling approaches in improving urban freight operations, evaluation of various policy implications, limitations, and future research

Agent-Based modeling of protests and violent confrontation: A micro-situational, multi-player, contextual rule-based approach

We propose an innovative Agent-Based model of street protests with multiple actors: police agents, three types of protesters (“hardcore”, “hangers- on” and “passers-by”), and “media” agents that seek to witness and publish episodes and situations of violence. Agents have multiple goals and action selection is performed using a “personality” vector together with context rules that provide adaptation. Protesters turn active or violent according to the threshold rule proposed by Epstein, and police agents arrest violent protesters within their move range if they have sufficient backup. The model was applied to a scenario where policemen defend a government building from protesters and described several emergent crowd patterns in real protests, such as clustering of violent and active protesters and formation of a confrontation line moving back and forth with localized fights. Violent behavior was restricted to the initially more aggressive protesters and did not propagate to the bulk of the crowd.info:eu-repo/semantics/acceptedVersio

Andean Land Use And Biodiversity: Humanized Landscapes In A Time Of Change

Some landscapes Cannot be understood without reference., to the kinds. degrees, kinds, degrees, and history of human-caused modifications to the Earth's surface. The tropical latitudes of the Andes represent one such place, with agricultural land-use systems appearing in the Early Holocene. Current land use includes both intensive and extensive grazing and crop- or tree-based agricultural systems found across virtually the, entire range of possible elevations and humidity regimes. Biodiversity found in or adjacent to such humanized landscapes will have been altered in abundance. composition, and distribution in relation to the resiliency of the native Species to harvest, hold cover modifications, and other deliberate or inadvertent human land uses. In addition, the geometries of land cover, resulting flout difference among the shapes, sizes, connectivities, and physical structures of the patches, corridors, and matrices that compose landscape mosaics, will constrain biodiversity, often in predictable ways. This article proposes a conceptual model that alter ins that the Continued persistence of native species may depend as much oil the shifting Of Andean landscape mosaics as on species characteristics, themselves. Furthermore, mountains such as the Andes display long gradients of environmental Conditions that after in relation to latitude, soil moisture, aspect, and elevation. Global environmental change will shift these, especially temperature and humidity regimes along elevational gradients, causing Changes outside the historical range of variation for some species. Both land-use systems and Conservation efforts will need to respond spatially to these shifts in the future, at both landscape and regional scales.Geography and the Environmen