Month: May 2017

Soft computing-based traffic density estimation using automated traffic sensor data under Indian conditions

Traffic density is an indicator of congestion and the present study explores the use of data-driven techniques for real time estimation and prediction of traffic density. Data-driven techniques require large database, which can be achieved only with the help of automated sensors. However, the available automated sensors developed for western traffic may not work for heterogeneous and lane-less traffic. Hence, the performance of available automated sensors was evaluated first to identify the best inputs to be used for the chosen application.

Source: www.indiaenvironmentportal.org.in

The advantage of being slow: the quasi-neutral contact process

According to the competitive exclusion principle, in a finite ecosystem, extinction occurs naturally when two or more species compete for the same resources. An important question that arises is: when coexistence is not possible, which mechanisms confer an advantage to a given species against the other(s)? In general, it is expected that the species with the higher reproductive/death ratio will win the competition, but other mechanisms, such as asymmetry in interspecific competition or unequal diffusion rates, have been found to change this scenario dramatically. In this work, we examine competitive advantage in the context of quasi-neutral population models, including stochastic models with spatial structure as well as macroscopic (mean-field) descriptions. We employ a two-species contact process in which the “biological clock” of one species is a factor of α slower than that of the other species. Our results provide new insights into how stochasticity and competition interact to determine extinction in finite spatial systems. We find that a species with a slower biological clock has an advantage if resources are limited, winning the competition against a species with a faster clock, in relatively small systems. Periodic or stochastic environmental variations also favor the slower species, even in much larger systems.

 

The advantage of being slow: the quasi-neutral contact process
Marcelo Martins de Oliveira, Ronald Dickman

Source: arxiv.org

Algorithmic Design for Hybrid Collective Intelligence

The Algorithmic Design for Hybrid Collective Intelligence satellite (ADHEsIoN’17) is a one-day event in September 20, 2017, as part of the Conference on Complex Systems (CCS’17). This conference is the official annual conference of the Complex Systems Society and is scheduled to convene in September 17-22, 2017. The conference is interdisciplinary in nature, focusing on understanding how elements interact to give rise to global properties, along with how global properties can constrain these elements.

Overview

Across an increasingly broad spectrum of everyday life, artificial intelligence (AI) is challenging the utility of human intelligence. Yet modern AI often gains its power from exploiting big data resulting from human collective behaviors (e.g. web posting, crowdsourcing). Hence, while AI is often contrasted with human intelligence, both may be more synergistic than is usually admitted. We call for a reflection, on designs and processes that may oppose, or support, the intersection of AI and human intelligence, working towards an AI-enhanced, hybrid collective intelligence.

Submission Guidelines

We invite abstracts (~500 words; 1 Figure) for oral presentations (~20 min.) of work that address relevant challenges across a range of socio-technical domains including, but not limited to:​

  • AI-supported Team Collaboration: AI to promote smart pairing between individuals, tasks and resources, whilst preserving some control over the time of delivery; curating group dynamics for enhanced synchronicity and productivity whilst maintaining transparency;
  • Collective Decision Making: Promote enhanced collective decision making by exploiting the effect of simple rules on social network structures whilst avoiding discriminating effects;  
  • Collective Learning: Identify and exploit insight from past operations to support future actions (e.g. project bidding) whilst identifying and eliminating outliers in a robust, evidence-based way;  
  • Human-Computer Interaction: Elicit and aggregate information from online activity (e.g. user reputation) for various operations (e.g. online rating system) whilst dealing with ambiguity (e.g. self-contradictions, missing data) and malicious manipulations (e.g. spamming);
  • Open Science: Promote the reuse, redistribution and reproduction of research, whilst maintaining appropriate attribution of credit and rigor
  • Organizational Design: Organizations designed such that they promote enhanced collective functions (e.g. social learning, culture) whilst preserving accountability and auditability;
  • Rumor Propagation within Social/Collaborative Platforms: Maintaining their self-organized nature, whilst restricting the diffusion of falsehoods and emergence of ‘echo chambers’;
  • Science of Science: Using modern bibliographic data to identify fruitful research trajectories and develop robust productivity measures, whilst reducing the marginalization of underrepresented groups; 

Pervasive theoretical challenges across these exemplar domains include: 

  • Regulating self-organization of the collective in an auditable way;
  • Generating value from dormant information; 
  • Prediction and intrinsic limitations; 
  • Big vs. Useful Data;

 

Abstracts should be submitted at https://easychair.org/conferences/?conf=adhesion17. Deadline for submission is 30th of June 2017. All questions about submissions should be emailed to the organizers listed below.

Organizing committee

  • Dr Christos Ellinas (University of Bristol, Stevens Institute of Technology); 
  • Dr. Marc Santolini (Northeastern University; Harvard Medical School); 
  • Dr. Thomas Maillart (University of Geneva); 
  • Prof. Seth Bullock (University of Bristol); 

Source: ccs2017.wixsite.com