727 research outputs found
Multi-level agent-based modeling - A literature survey
During last decade, multi-level agent-based modeling has received significant
and dramatically increasing interest. In this article we present a
comprehensive and structured review of literature on the subject. We present
the main theoretical contributions and application domains of this concept,
with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic
statistics updated. v7 Change of the name of the paper to reflect what it
became, many refs and text added, bibliographic statistics update
Improving Robustness in Social Fabric-based Cultural Algorithms
In this thesis, we propose two new approaches which aim at improving robustness in social fabric-based cultural algorithms. Robustness is one of the most significant issues when designing evolutionary algorithms. These algorithms should be capable of adapting themselves to various search landscapes. In the first proposed approach, we utilize the dynamics of social interactions in solving complex and multi-modal problems. In the literature of Cultural Algorithms, Social fabric has been suggested as a new method to use social phenomena to improve the search process of CAs. In this research, we introduce the Irregular Neighborhood Restructuring as a new adaptive method to allow individuals to rearrange their neighborhoods to avoid local optima or stagnation during the search process. In the second approach, we apply the concept of Confidence Interval from Inferential Statistics to improve the performance of knowledge sources in the Belief Space. This approach aims at improving the robustness and accuracy of the normative knowledge source. It is supposed to be more stable against sudden changes in the values of incoming solutions. The IEEE-CEC2015 benchmark optimization functions are used to evaluate our proposed methods against standard versions of CA and Social Fabric. IEEE-CEC2015 is a set of 15 multi-modal and hybrid functions which are used as a standard benchmark to evaluate optimization algorithms. We observed that both of the proposed approaches produce promising results on the majority of benchmark functions. Finally, we state that our proposed strategies enhance the robustness of the social fabric-based CAs against challenges such as multi-modality, copious local optima, and diverse landscapes
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent âdevicesâ, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew âcognitive devicesâ are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Psychopower and Ordinary Madness: Reticulated Dividuals in Cognitive Capitalism
Despite the seemingly neutral vantage of using nature for widely-distributed computational purposes, neither post-biological nor post-humanist teleology simply concludes with the real "end of nature" as entailed in the loss of the specific ontological status embedded in the identifier "natural." As evinced by the ecological crises of the Anthropoceneâof which the 2019 Brazil Amazon rainforest fires are only the most recentâour epoch has transfixed the ânatural order" and imposed entropic artificial integration, producing living species that become âanoetic,â made to serve as automated exosomatic residues, or digital flecks. I further develop Gilles Deleuzeâs description of control societies to upturn Foucauldian biopower, replacing its spacio-temporal bounds with the exographic excesses in psycho-power; culling and further detailing Bernard Stieglerâs framework of transindividuation and hyper-control, I examine how becoming-subject is predictively facilitated within cognitive capitalism and what Alexander Galloway terms âdeep digitality.â Despite the loss of material vestiges qua virtualizationâwhich I seek to trace in an historical review of industrialization to postindustrializationâthe drive-based and reticulated "internet of things" facilitates a closed loop from within the brain to the outside environment, such that the aperture of thought is mediated and compressed. The human brain, understood through its material constitution, is susceptible to total dataficationâs laminated process of âbecoming-mnemotechnical,â and, as neuroplasticity is now a valid description for deep-learning and neural nets, we are privy to the rebirth of the once-discounted metaphor of the âcybernetic brain.â Probing algorithmic governmentality while posing noetic dreaming as both technical and pharmacological, I seek to analyze how spirit is blithely confounded with machine-thinkingâs gelatinous cognition, as prosthetic organ-adaptation becomes probabilistically molded, networked, and agentially inflected (rather than simply externalized)
Genetic and Swarm Algorithms for Optimizing the Control of Building HVAC Systems Using Real Data: A Comparative Study.
Buildings consume a considerable amount of electrical energy, the Heating, Ventilation,
and Air Conditioning (HVAC) system being the most demanding. Saving energy and maintaining
comfort still challenge scientists as they conflict. The control of HVAC systems can be improved by
modeling their behavior, which is nonlinear, complex, and dynamic and works in uncertain contexts.
Scientific literature shows that Soft Computing techniques require fewer computing resources
but at the expense of some controlled accuracy loss. Metaheuristics-search-based algorithms show
positive results, although further research will be necessary to resolve new challenging multi-objective
optimization problems. This article compares the performance of selected genetic and swarmintelligence-
based algorithms with the aim of discerning their capabilities in the field of smart buildings.
MOGA, NSGA-II/III, OMOPSO, SMPSO, and Random Search, as benchmarking, are compared
in hypervolume, generational distance, Δ-indicator, and execution time. Real data from the Building
Management System of Teatro Real de Madrid have been used to train a data model used for the
multiple objective calculations. The novelty brought by the analysis of the different proposed dynamic
optimization algorithms in the transient time of an HVAC system also includes the addition,
to the conventional optimization objectives of comfort and energy efficiency, of the coefficient of
performance, and of the rate of change in ambient temperature, aiming to extend the equipment
lifecycle and minimize the overshooting effect when passing to the steady state. The optimization
works impressively well in energy savings, although the results must be balanced with other real
considerations, such as realistic constraints on chillersâ operational capacity. The intuitive visualization
of the performance of the two families of algorithms in a real multi-HVAC system increases
the novelty of this proposal.post-print888 K
Multi-Objective UAV Mission Planning Using Evolutionary Computation
This investigation purports to develop a new model for multiple autonomous aircraft mission routing. Previous research both related and unrelated to this endeavor have used classic combinatoric problems as models for Unmanned Aerial Vehicle (UAV) routing and mission planning. This document presents the concept of the Swarm Routing Problem (SRP) as a new combinatorics problem for use in modeling UAV swarm routing, developed as a variant of the Vehicle Routing Problem with Time Windows (VRPTW). The SRP removes the single vehicle per target restraint and changes the customer satisfaction requirement to one of vehicle on location volume. The impact of these alterations changes the vehicle definitions within the problem model from discrete units to cooperative members within a swarm. This represents a more realistic model for multi-agent routing as a real world mission plan would require the use of all airborne assets across multiple targets, without constraining a single vehicle to a single target. Solutions to the SRP problem model result in route assignments per vehicle that successfully track to all targets, on time, within distance constraints. A complexity analysis and multi-objective formulation of the VRPTW indicates the necessity of a stochastic solution approach leading to the development of a multi-objective evolutionary algorithm. This algorithm design is implemented using C++ and an evolutionary algorithm library called Open Beagle. Benchmark problems applied to the VRPTW show the usefulness of this solution approach. A full problem definition of the SRP as well as a multi-objective formulation parallels that of the VRPTW method. Benchmark problems for the VRPTW are modified in order to create SRP benchmarks. These solutions show the SRP solution is comparable or better than the same VRPTW solutions, while also representing a more realistic UAV swarm routing solution
Internet of Robotic Things Intelligent Connectivity and Platforms
The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and âthingsâ have evolved significantly. âThingsâ now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of âintelligent thingsâ (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.publishedVersio
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