Modeling of Distribution Service Network System in Comprehensive Passenger Transportation Hub

2012 ◽  
Vol 253-255 ◽  
pp. 1195-1200
Author(s):  
Zhe Zhang ◽  
Chang Xu Ji ◽  
Mao Jing Jin ◽  
Qian Li ◽  
Lifen Yun ◽  
...  
Keyword(s):  
Dynamic Method ◽  
Network System ◽  
Service Network ◽  
Individual Agent ◽  
Nonlinear Characteristics ◽  
Passenger Transportation ◽  
Environment And Behavior ◽  
Multi Agent ◽  
And Behavior ◽  
Structure Environment

Distribution service network system (DSNS) has dynamic, open, pop and other nonlinear characteristics in terms of structure, environment, and behavior as a subsystem of comprehensive passenger transportation hub system (CPTH). It is a typical complex system. The author putted forward the adaptability of DSNS based on the analysis of complexity of DSNS and analyzed the driving force of adaptability. The model of individual agent and self-adaptive control model of DSNS were designed to provide a dynamic method for adjusting control strategy based on multi-Agent method and CAS theory.

scholarly journals Learning Swarm Behaviors using Grammatical Evolution and Behavior Trees

2019 ◽  
Author(s):  
Aadesh Neupane ◽  
Michael Goodrich
Keyword(s):  
Fitness Function ◽  
Grammatical Evolution ◽  
Individual Agent ◽  
Collective Behaviors ◽  
Fitness Functions ◽  
Swarm Behavior ◽  
Behavior Trees ◽  
Multi Agent ◽  
Nest Maintenance ◽  
And Behavior

Algorithms used in networking, operation research and optimization can be created using bio-inspired swarm behaviors, but it is difficult to mimic swarm behaviors that generalize through diverse environments. State-machine-based artificial collective behaviors evolved by standard Grammatical Evolution (GE) provide promise for general swarm behaviors but may not scale to large problems. This paper introduces an algorithm that evolves problem-specific swarm behaviors by combining multi-agent grammatical evolution and Behavior Trees (BTs). We present a BT-based BNF grammar, supported by different fitness function types, which overcomes some of the limitations in using GEs to evolve swarm behavior. Given human-provided, problem-specific fitness-functions, the learned BT programs encode individual agent behaviors that produce desired swarm behaviors. We empirically verify the algorithm's effectiveness on three different problems: single-source foraging, collective transport, and nest maintenance. Agent diversity is key for the evolved behaviors to outperform hand-coded solutions in each task.

Review of Resources in environment and behavior.

1979 ◽  
Vol 24 (10) ◽  
pp. 879-879
Author(s):  
KARL E. WEICK
Keyword(s):  
Environment And Behavior ◽  
And Behavior

scholarly journals Special Issue on Mental Health and Well-Being in Adolescence: Environment and Behavior

2021 ◽  
Vol 18 (6) ◽  
pp. 2975
Author(s):  
Javier Ortuño-Sierra ◽  
Beatriz Lucas-Molina ◽  
Félix Inchausti ◽  
Eduardo Fonseca-Pedrero
Keyword(s):  
Mental Health ◽  
Well Being ◽  
Psychological Problems ◽  
Special Issue ◽  
Children And Adolescent ◽  
Environment And Behavior ◽  
And Behavior ◽  
Health And Well Being

Psychological problems in children and adolescent populations range from 10% to 20% [...]

A Geometric Approach to Dynamically Feasible, Real-Time Formation Control

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
D. H. A. Maithripala ◽  
D. H. S. Maithripala ◽  
S. Jayasuriya
Keyword(s):  
Real Time ◽  
Wide Class ◽  
Formation Control ◽  
Geometric Approach ◽  
Control Problems ◽  
Multi Agent Systems ◽  
Individual Agent ◽  
Planning Algorithm ◽  
Explicit Consideration ◽  
Multi Agent

We propose a framework for synthesizing real-time trajectories for a wide class of coordinating multi-agent systems. The class of problems considered is characterized by the ability to decompose a given formation objective into an equivalent set of lower dimensional problems. These include the so called radar deception problem and the formation control problems that fall under formation keeping and/or formation reconfiguration tasks. The decomposition makes the approach scalable, computationally economical, and decentralized. Most importantly, the designed trajectories are dynamically feasible, meaning that they maintain the formation while satisfying the nonholonomic and saturation type velocity and acceleration constraints of each individual agent. The main contributions of this paper are (i) explicit consideration of second order dynamics for agents, (ii) explicit consideration of nonholonomic and saturation type velocity and acceleration constraints, (iii) unification of a wide class of formation control problems, and (iv) development of a real-time, distributed, scalable, computationally economical motion planning algorithm.

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