Concept of Client-Server Environment for Agent-Based Modeling and Simulation of Living Systems

Concept of Client-Server Environment for Agent-Based
Modeling and Simulation of Living Systems
Ingars Ribners and Guntis Arnicāns
(ir13073@lu.lv, guntis.arnicans@lu.lv)
3 June 2015
Rīga, Latvia

Agent-Based Modeling Paradigm
System – a composition (structure) of autonomous entities – agents.
An example of typical agent based model (Netlogo)
Modeling paradigm
inspired by nature

Agent – a key abstraction in this modeling approach.
Agent means a subject that acts in some environment.

Main qualities of agent as described by Jennings et.al (1998):
• Situatedness;
• Autonomy;
• Flexibility (responsiveness, pro-activeness, social behaviour)

Properties of Living Systems
General Living Systems (GLS) theory – James G. Miller (1978, 1991)
Living System – a special subclass of open system

Eight hierarchical levels of living systems:
cells, organs, organisms, groups, organizations, communities,
societies, supranational systems.

20 standard functional subsystems of a living system:
reproducer, boundary, ingestor, distributor, converter, producer, storage,
extruder, motor, supporter, input transducer, internal transducer, channel and
net, timer, decoder, associator, memory, decider, encoder, output transducer.

Modeling and Simulation Environment
Goal:
1. To work out a general and extensible language for describing
models of systems in agent-based paradigm;
2. To work out an environment for «execution» of models
described in above language that would be easy enough to
be used by non-programmers.
We are using General Living Systems theory as a reference.

Features of Living Systems
(that should be supported by modeling environment)
Large scale concurrent models
(up to 104-105 agents)

Comprehensive environment structures

Comprehensive environment structures
Temperature, gravitation acceleration,
light, ... and their change pattern (t)
Time
model
Space
model
year cycle...
Day cycle,
gravitation field...
Place, altitude...
An example:

Material interaction
• Environment constraints to the ability of perception;
Visibility limit

Material interaction
• Environment constraints to the ability of acting.
m
𝐹
→
(if m>0)
-> constraints on ,𝑣→ 𝑥→
Example 1
Example 2
Influence of material environment
could be limiting as well as promoting

Non-material interaction

Individual evolution process

Memory, skills, knowledge, reasoning
Ability to discover a structure in the neighborhood

Client/server architecture
Other features of the modeling environment

• High level operations with sets;
• Synchronous or asynchronous simulation;
• Support of intervention into the running system;
• "Avatar" feature;
• Node management tools;
• Openness (i.e. FIPA).
Other features of the modeling environment

Main Concepts
Agent, Event, Environment, Communication arena, Artifact

• A prototype of modeling environment with demo system is implemented
to illustrate some of the concepts. Only wakeup functionality (once per
second);
• on one Erlang/OTP 17.5 node on (PC i5-4460, 4-cores, 3.2GHz, 16GB RAM,
Windows 8)
Prototype

Benchmarks
Number of
agents
Start time
(ms)*
Memory
used (MB)**
Memory used
by agent (kB)
100 17 20,00 35,00
500 22 25,40 17,80
1000 37 32,10 15,60
5000 194 85,60 13,82
10000 530 152,40 13,59
50000 8007 726,90 14,21
100000 28451 1402,50 13,86
* Average from 4 measurements
** Approx. value from Windows 8 Task Manager
Thank You!

Concept of Client-Server Environment for Agent-Based Modeling and Simulation of Living Systems

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Ähnlich wie Concept of Client-Server Environment for Agent-Based Modeling and Simulation of Living Systems

Ähnlich wie Concept of Client-Server Environment for Agent-Based Modeling and Simulation of Living Systems (20)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

Concept of Client-Server Environment for Agent-Based Modeling and Simulation of Living Systems