[go: up one dir, main page]

Siebecker, 2003 - Google Patents

A Hidden Markov Model for describing the statistical evolution of social groups over communication networks

Siebecker, 2003

View PDF
Document ID
11674896804845419977
Author
Siebecker D
Publication year

External Links

Snippet

The goal of this thesis is the development of an abstract statistical model of the evolution for social networks (communities). Our approach is to specify a set of general models that govern the behavior on a micro-scale level (the micro-laws of the model) and observe the …
Continue reading at www.cs.rpi.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/04—Architectures, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/12—Computer systems based on biological models using genetic models
    • G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G06N5/043—Distributed expert systems, blackboards
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/005—Probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/02—Computer systems based on specific mathematical models using fuzzy logic
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management

Similar Documents

Publication Publication Date Title
Bertsekas et al. Rollout algorithms for stochastic scheduling problems
Giraud‐Carrier A note on the utility of incremental learning
Yu et al. Emotional multiagent reinforcement learning in spatial social dilemmas
Van Den Bergh An analysis of particle swarm optimizers
Otero et al. A new sequential covering strategy for inducing classification rules with ant colony algorithms
Liu et al. Autonomy-oriented computing (AOC): Formulating computational systems with autonomous components
Casillas et al. Learning cooperative linguistic fuzzy rules using the best–worst ant system algorithm
US7171393B2 (en) Solving constraint satisfaction problems using variable-range hopping
Mukhopadhyay et al. Reinforcement learning algorithms for uncertain, dynamic, zero-sum games
Bartal et al. Member behavior in dynamic online communities: Role affiliation frequency model
Bullock et al. Agent heterogeneity mediates extremism in an adaptive social network model
Rezvanian et al. Learning automata theory
Siebecker A Hidden Markov Model for describing the statistical evolution of social groups over communication networks
Pluhacek et al. PSO with partial population restart based on complex network analysis
Fortier et al. Learning Bayesian classifiers using overlapping swarm intelligence
Acerbi et al. Continuous time bayesian networks for gene network reconstruction: a comparative study on time course data
Nagy et al. A genetic algorithm for the minimum vertex cover problem with interval-valued fitness
Hakli A qualified search strategy with artificial bee colony algorithm for continuous optimization
Tanay et al. Stochastic diffusion search applied to trees: a swarm intelligence heuristic performing monte-carlo tree search
Sheldon Manipulation of PageRank and Collective Hidden Markov Models
Koudil et al. Solving partitioning problem in codesign with ant colonies
Chen et al. Inferring agent dynamics from social communication network
Hansen Comparative performance of backpropagation networks designed by genetic algorithms and heuristics
Demir et al. Generating effective initiation sets for subgoal-driven options
CN120429510B (en) Complex social behavior simulation and public opinion deduction method based on multiple intelligent agents